Marzieh Karimi; Hasan Khademi zare; Yahia Zare Mehrjerdi; Mohammad-Bagher Fakhrzad
Abstract
Vendor-managed inventory (VMI) is a popular inventory management system that allows a vendor to access sales data and manage inventory levels for his retailers. The formulation of service level and pricing decisions are finite in the VMI model literature. The study examines how a manufacturer and its ...
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Vendor-managed inventory (VMI) is a popular inventory management system that allows a vendor to access sales data and manage inventory levels for his retailers. The formulation of service level and pricing decisions are finite in the VMI model literature. The study examines how a manufacturer and its retailer communicate with one another to optimize their net profits through modifying service level, pricing, and inventory policy in a VMI system employing a Stackelberg game. The manufacturer produces a product and distributes it to several retailers at a similar wholesale price. The retailers subsequently offer the product at retail pricing in independent marketplaces. The Cobb-Douglas demand function could characterize the demand rate in every market, which is an enhancing function of the service level, however, a reducing function of retail prices. The manufacturer selects its wholesale pricing, replenishment cycles, backorder amount, and binary variable for production capacity to optimize profit. Retailers determine retail pricing and service levels so that they may optimize their profitability. Solution procedures are evolved for finding the Stackelberg game equilibrium from which no firm is inclined to deviate from maximizing its profit. The balance benefits the manufacturer while increasing the revenues of the retailers. If the retailers are prepared to engage with the manufacturer via a cooperative contract, the equilibrium could be enhanced to the advantage of both the manufacturer and his retailers. Ultimately, a numerical example is shown, along with the appropriate sensitivity analysis, to demonstrate that. 1) In certain circumstances, the manufacturer might benefit from his leadership and monopolize the additional profit generated by the VMI system. 2) The manufacturer's profit, and later the retailers' profit, could be increased more by the cooperative contract, in comparison to the Stackelberg equilibrium; 3) Market-related parameters have a substantial impact on the net profit of any enterprise.
Ehsan Vaezi; Seyyed Esmaeil Najafi; Seyed mohamad Haji Molana; Farhad Hosseinzadeh Lotfi; Mahnaz Ahadzadeh Namin
Abstract
Data Envelopment Analysis (DEA) is one of the methods most widely used for measuring the relative efficiency of DMUs in the world today. The efficiency evaluation of the network structure opens the “black box” and considers the internal structure of systems. In this paper, a three-stage ...
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Data Envelopment Analysis (DEA) is one of the methods most widely used for measuring the relative efficiency of DMUs in the world today. The efficiency evaluation of the network structure opens the “black box” and considers the internal structure of systems. In this paper, a three-stage network model is considered with additional inputs and undesirable outputs and obtains the efficiency of the network, as interval efficiency in presence of the imprecise datum. The proposed model of this paper simulates a factory in the factual world with a production area, three warehouses and two delivery points. This factory is taken into consideration as a dynamic network and a multiplicative DEA approach is utilized to measure efficiency. Given the non-linearity of the models, a heuristic method is used to linearize the models. Ultimately, this paper concentrates on the interval efficiency to rank the units. The results of this ranking demonstrated that the time periods namely, (24) and (1) were the best and the poorest periods, respectively, in context to the interval efficiency within 24 phases of time.
Javad Behnamian; Zeynab Rahami
Abstract
Assembly lines are flow-oriented production systems that are of great importance in the industrial production of standard, high-volume products and even more recently, they have become commonplace in producing low-volume custom products. The main goal of designers of these lines is to increase the efficiency ...
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Assembly lines are flow-oriented production systems that are of great importance in the industrial production of standard, high-volume products and even more recently, they have become commonplace in producing low-volume custom products. The main goal of designers of these lines is to increase the efficiency of the system and therefore, the assembly line balancing to achieve an optimal system is one of the most important steps that have to be considered in the design of assembly lines. The purpose of the assembly line balancing is to assign tasks to the workstation called the station, so that prerequisite relationships, cycle times, and other assembly line constraints to be met and a number of line performance criteria to be optimized. In this study, considering the social responsibility related objective function, a mathematical model is proposed for scheduling and balancing the cost-oriented assembly line that has resource constraints with cost uncertainty. The box set robust optimization is applied and the obtained model is solved with the augmented epsilon constraint in the GAMS and some test problems and their results are presented. Finally, the cost parameter has been changed in a robust optimization approach and the obtained results have been analyzed for different costs.
Nazila Adabavazeh; Mehrdad Nikbakht; Alireza Amirteimoori
Abstract
Communities are constantly seeking to manage the damages which are caused by crises. In this regard, health centers have become the most expensive unit of the health system as they provide quick and timely health care services to reduce the effects of unexpected accidents. So, their planning and preparation ...
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Communities are constantly seeking to manage the damages which are caused by crises. In this regard, health centers have become the most expensive unit of the health system as they provide quick and timely health care services to reduce the effects of unexpected accidents. So, their planning and preparation should be considered as an important part of strategic health policies. The purpose of this study is to investigate performance evaluation techniques for health units, which is helpful for WHO to identify the capabilities of crisis management and the limitations of world health units. This study evaluates the performance of the world health systems dealing with Corona-virus based on parametric and nonparametric statistical techniques according to "Population, GPD Per Capita, Total Recovered, Total Cases, and Total Deaths". This descriptive cross-sectional study is performed on the World Population Review, Worldometer, WHO data of Covid-19 from 1 March -11 April 2020. Based on the results, the efficient and inefficient health system units are identified. The results of this study show that 52 medical centers have not performed efficiently. The average efficiency of inefficient units is 0.30. On this basis, most of the studied countries do not operate efficiently due to the lack of optimal use of resources. Ineffective health system units call for greater attention of WHO in promoting health culture during the crisis management of common viruses. Therefore, there is a capacity to improve efficiency by 70%. By conducting this research, in addition to the introduction of functional patterns to the top health managers, it is possible to plan more accurately to develop the capacity of health care services and save resources.
Adel Pourghader Chobar; Mohammad Amin Adibi; Abolfazl Kazemi
Abstract
Hubs facilitate aggregation of connection, and switching points of material and people flow to reduce costs as well as environmental pollution. Hub Location Problem (HLP) is a relatively new research field of classical location issues. In this regard, this paper provides a tourist hub location problem ...
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Hubs facilitate aggregation of connection, and switching points of material and people flow to reduce costs as well as environmental pollution. Hub Location Problem (HLP) is a relatively new research field of classical location issues. In this regard, this paper provides a tourist hub location problem to procure essential commodities, which characterized with non-negligible dynamics of demand. Dealing with a high level of change in demand for these goods over time, the possibility of establishment, renovation, or renting the distribution centers have been formulated in the proposed mathematical model. Finding the best location for distribution centers, the model aims to minimize the routing cost between production centers and retailers, along with emitting pollution from vehicles as less as possible. As the proposed model is bi-objective, that is minimizing costs and pollution emission, two Pareto-based solution methodologies, namely the non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA), are used. Since the obtained results from these algorithms are highly dependent on the value of parameters, the Taguchi method is adopted to tune the parameters of two solution methodologies. Finally, to verify the proper performance of two solution methodologies, numerical examples in different scales are generated. The obtained results from all scales and solution methodologies indicate that the new modeling approach to the possibility of establishment, renovation, or renting the distribution centers results in lower costs and pollution emission. The results indicate that supply chain costs and environmental impacts increase by increasing the demand. The number of established distribution hubs also increases by increasing the demand.
Naser Ghasemi; Esmaeil Najafi; Farhad Hosseinzadeh Lotfi; Farzad Movahedi Sobhani
Abstract
Most organizations and companies have hierarchical structures, and appropriate models are required to measure the efficiency of this kind of network systems. Data envelopment analysis (DEA) is a well-known method introduced for measuring the relative efficiency of a set of decision-making units (DMUs) ...
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Most organizations and companies have hierarchical structures, and appropriate models are required to measure the efficiency of this kind of network systems. Data envelopment analysis (DEA) is a well-known method introduced for measuring the relative efficiency of a set of decision-making units (DMUs) that use multiple inputs to produce multiple outputs. Conventional DEA models usually generate misleading results while evaluating the performance of network systems. The present study aims at developing suitable models for measuring the efficiency of hierarchical structures using the centralized and non-cooperative leader-follower game models. In the proposed method, the divisional efficiencies (within an organization) and the overall efficiency of the organization are calculated. The proposed models are applied to assess the performance of 20 schools in Iran. The results of the two proposed models show that none of the schools are efficient, suggesting that these schools do not optimally utilize their resources. The application of the results of the proposed models enables managers to identify inefficient sub-units and develop strategies to improve their performance.
Sarvenaz Heydarpour; Seyyed Hosein Seyyed Esfahani; Behrooz Khorshidvand
Abstract
Regarding contractors are one of the fundamental features of construction and industrial projects, therefore the selection of contractors is one of the major decisions of managers and decision-makers. This paper uses the multi-criteria decision-making method Analytic Hierarchy Process (AHP) to incorporate ...
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Regarding contractors are one of the fundamental features of construction and industrial projects, therefore the selection of contractors is one of the major decisions of managers and decision-makers. This paper uses the multi-criteria decision-making method Analytic Hierarchy Process (AHP) to incorporate the weightings of input and output variables into Data Envelopment Analysis (DEA) for evaluation and ranking of contractors (Zarand Iranian Steel Company). At first, according to previous research, the most effective and important evaluation indicators of contractors are selected, then in the proposed model with the AHP approach, seven input indicators and three output indicators are weighted and ranked, and the performance of 20 contractors from one of the company's projects is determined and ranked with the input-oriented CCR model. By applying this approach, decision-makers and practitioners can effectively compare operational efficiency between contractors, and therefore generate more informed and they can provide appropriate solutions to increase the efficiency of other contractors.
Hassan Rashidi; Zeynab Rashidi; Latifeh Pour Mohammad Bagher; Mohammad Bahrani
Abstract
In today's world, software tools play an important role in speeding up software development, reducing development costs and human efforts, as well as increasing reliability. In software development by tools, choosing a suitable tool will be a difficult task because many of them are available with different ...
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In today's world, software tools play an important role in speeding up software development, reducing development costs and human efforts, as well as increasing reliability. In software development by tools, choosing a suitable tool will be a difficult task because many of them are available with different capabilities. On the other hand, little research has focused on the classification of these tools and their comparison. This paper aims to perform a literature review of software development tools and to propose architectures for the requirement of the Organization of Small Industries and Industrial Towns of Iran (OSIITI), in Iran. We did a survey over more than 50 software development and programming tools. The results of this survey identified ten classes, namely (a) Database Tools; (b) Integrated Development Environment; (c) Software Development Frameworks; (d) Data Science Tools; (e) Source Control Tools; (f) DevOps Tools; (g) Unified modeling Language (UML) Tools; (h) Cloud Tools for Software Development; (h) Prototyping Tools; and (j) Notifications Programs. For each class, we collected the most software tools that are currently used with their major features. After that, two architectures, based on layered and service-oriented patterns are proposed for OSIITI. The ten specified classes, along with the tools in each class, are very useful for organizations like OSIITI who want to develop software, for both small and large projects.
Hasan Hosseini Nasab; Mahdi Tavana Chehartaghi
Abstract
Competitive advantage in features, number of branches, or location of any company enables it to provide better services to customers than competitors. In this article, the issue of location in a situation where competitors can decide based on competitor conditions to maximize their profits is examined. ...
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Competitive advantage in features, number of branches, or location of any company enables it to provide better services to customers than competitors. In this article, the issue of location in a situation where competitors can decide based on competitor conditions to maximize their profits is examined. First, based on the conditions and characteristics of each competitor, including the number of branches and budget limit, the performance range of each competitor is determined as the radius of effect. Two mathematical formulas are presented for the player and using the concepts of game theory, each player's market share in the competitive environment is determined to earn maximum profit. To solve the problem, first, the initial answers were obtained through the ant colony algorithm, then these answers were entered as input to the Simulated Annealing algorithm, which has a high speed to obtain the answer. The models developed for the two supermarkets have been evaluated and the results have been approved by experts.
Ali Goodarzi; Ali Mostafaeipour; Hasan Hosseini Nasab; Yahia Zare Mehrjerdi
Abstract
A multi-level sustainable supply chain is related to a system that includes all activities necessary to transfer and supply materials and services from the producer to the consumer. In this system, the focus is on providing materials and services based on a number of objectives, such as reducing costs, ...
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A multi-level sustainable supply chain is related to a system that includes all activities necessary to transfer and supply materials and services from the producer to the consumer. In this system, the focus is on providing materials and services based on a number of objectives, such as reducing costs, increasing quality, and preserving the environment. Due to the increase of uncertainty in the supply chain, organizations need to use resources for the prediction of internal uncertainties, needs, and supply, thereby minimizing vulnerability and elevating the tolerance of their supply. Understanding the uncer-tainties and the parameters causing factors causes the problem of risk management to be raised in some cases. Therefore, main contribution of current study is multi-objective planning for a sustainable, multi-level, multi-period model, consid-ering the determined conditions and boom as uncertainty scenarios, has been specifically considered. The most important goal of the research is to determine the best units of each level (suppliers, factories, ...) of chain networks according to the points and criteria determined in the model and network, design and determine the best communication routes (network) between the selected units Each level is optimal with other levels as well as determining the volume of transported goods in these routes. For this purpose, a mathematical model has been developed, which is solved through the limited epsilon method and NSGA-II meta-heuristic algorithm. Data comparing the mathematical model and NSGA-II meta-heuristic algorithm show the calculated errors of 0.022, which considering that it is less than 0.1, the calculation error is acceptable and can be compared to the results of the error methods. The sensitivity analysis on the probability of the boom scenario showed the value of the objective function can change between 7398.51 and 3245.73. Finally, the sensitivity analysis of the probability of recession scenario showed the value of the objective function can change between 3291.64 and 9364.35. The findings of this research show that using the multi-objective planning model in the sustainable supply chain, taking into account the boom and bust of the market, can create significant improvements in the performance and profitability of the supply chain.
Behnam Ayyoubzadeh; Sadoullah Ebrahimnejad; Mahdi Bashiri; Vahid Bardaran; Seyed Mohammad Hasan Hosseini
Abstract
This paper aims to confront the uncertainties in the flexible job shop scheduling (FJSS) problem by considering the tax regulations of energy consumption and timely delivery. Uncertainties include all unexpected disruptions such as machine breakdowns, modifications or cancellation of the orders, and ...
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This paper aims to confront the uncertainties in the flexible job shop scheduling (FJSS) problem by considering the tax regulations of energy consumption and timely delivery. Uncertainties include all unexpected disruptions such as machine breakdowns, modifications or cancellation of the orders, and receiving new orders that lead to failure in initial scheduling. Two strategies with the energy-saving approach have been proposed based on scheduling repair. Two considered objective functions are to minimize the tax cost on surplus energy consumption and to minimize total cost of jobs tardiness. The problem is described with the parameters and decision variables clearly in the form of MIP model. Moreover, the proposed model is investigated using data of a real case study in a company based on casting processes. Since the problem is well known strongly NP-hard, a new approach is introduced based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find proper solutions for decision-makers. The computational results show that the proposed model and solution approach repairs properly the original scheduling and could improve the Pareto front comparing with the original scheduling. Due to the result, two proposed strategies could reduce total cost of jobs tardiness more than 47.56% compared with the original scheduling in eight different cases. It could also improve the second objective more than 56.91%. This approach will help the manufacturing industry managers, especially in make-to-order (MTO) systems with high-powered machines to respond rapidly to unexpected disruptions with the lowest energy consumption and tardiness penalty.
Monireh Hosseini; Zohreh Tammimy; Elnaz Galavi
Abstract
Social networks provide marketing managers and businesses with opportunity to target their customers. By understanding the demographics of users, marketing managers can offer suitable products and services. Although direct questioning can be drawn upon to solicit users’ demographics such as age, ...
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Social networks provide marketing managers and businesses with opportunity to target their customers. By understanding the demographics of users, marketing managers can offer suitable products and services. Although direct questioning can be drawn upon to solicit users’ demographics such as age, some customers due to privacy concerns do not like to reveal their personal information and, it cannot come in handy for potential customer identification. The huge amount of data social networks generate can solve this problem. Previous studies in the prediction of demographic characteristics suffer some limitations because they were mainly text based and hence, language-bound. This study investigates how some interactive data can predict users’ age. Further, it examines if classification methods can be used for age prediction. The results revealed that the number of friends, number of opposite sex friends, number of comments received, and number of photos which users share can predict users’ age. Also, a linear relationship between interactive data and users’ age was found.
Adekola Olayinka Oke; Joel Ashem Abafi; Banji Zacheous Adewole
Abstract
Equipment breakdown adds to the cost of production and considerably affect the overall equipment efficiency in automated lines due to unplanned downtime. Preventive maintenance with appropriate actions has been considered to enhance products quality, equipment reliability and minimize the probability ...
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Equipment breakdown adds to the cost of production and considerably affect the overall equipment efficiency in automated lines due to unplanned downtime. Preventive maintenance with appropriate actions has been considered to enhance products quality, equipment reliability and minimize the probability of system brake down or failure. To this end, this study conducted a reliability status of nine packaging facilities, from the perspective of existing failure data of production system in the Nigerian multinational bottling plant. Failure data of the production system were stratified and analyzed to achieve the failure interval of each of the facilities and the sub-systems. Stratification of failure data resulted to an established input format that fitted the Pareto chart analysis, Weibull Distributions and Reliability/Failure Time analysis. The results showed that the facility with minimum value of reliability was filler machine. A standby filler system was therefore recommended in order to prevent unnecessary idleness of the other facilities especially when the production target is high. The study concluded that, analysis of downtime in a production/manufacturing system assisted in predicting the likely failure interval and hence a preventive maintenance scheduled was proposed.
Mostafa Zaree; Reza Kamranrad; Mojtaba Zaree; Iman Emami
Abstract
Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources. Therefore, managing and scheduling a project is a necessity for the project. The timing of a project is to specify a sequence of times for a series of related activities. According ...
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Today's competitive conditions have caused the projects to be carried out in the least possible time with limited resources. Therefore, managing and scheduling a project is a necessity for the project. The timing of a project is to specify a sequence of times for a series of related activities. According to their priority and their latency, so that between the time the project is completed and the total cost is balanced. Given the balance between time and cost, and to achieve these goals, there are several options that should be considered among existing options and ultimately the best option to perform activities to complete the project. In this research, a mathematical model of project scheduling with multiple goals based on cost patterns and consideration of resource constraints is presented, and this problem is considered as a problem for NP-hard issues in family hybrid optimization. GA، PSO and SA Meta-heuristic algorithms are used to solve the proposed model in project scheduling and the results are compared with each other.
Seyedeh Ladan Fadaei Foroutan; Shahrooz Bamdad
Abstract
Railways are considered the efficient transport system that provides the possibility of transportation through a rail network. Railway stations are the major part of the rail transport system and evaluating its performance is of particular importance, since various activities such as passenger transport, ...
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Railways are considered the efficient transport system that provides the possibility of transportation through a rail network. Railway stations are the major part of the rail transport system and evaluating its performance is of particular importance, since various activities such as passenger transport, and welfare and commercial services are provided in this part of the system. In this research, the efficiency of Iranian railway stations in 19 zones is measured by data envelopment analysis (DEA), and the efficient centers and reference units for inefficient centers have been identified by analyzing the efficiency of stations. Railway stations are analyzed using an output-oriented slack-based measure (SBM) model with a constant returns to scale. The performance of station was evaluated by the input index of total station area, number of platforms, number of staff, number of available seats, total cost of station, output index of number of passengers transported, number of trains stopped, and total revenue of the station. The ranking results showed that Tehran, Mashhad, Shahroud, Zanjan, Qom, and Kerman stations had the highest level of efficiency. Finally, for inefficient stations, the surplus values of inputs and slack values of outputs were provided to improve the efficiency.
Mojtaba Afsharian; Bijan Baghbani; Masoumeh Lajevardi; Amin Saeidi khasraghi; Mohammad Reza Sasouli
Abstract
In today's era, organizations recognize the challenges of meeting the evolving needs and preferences of customers. Simply improving products and individual performance is insufficient to satisfy customer requirements. Instead, organizations have embraced a collaborative strategy, utilized efficient supply ...
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In today's era, organizations recognize the challenges of meeting the evolving needs and preferences of customers. Simply improving products and individual performance is insufficient to satisfy customer requirements. Instead, organizations have embraced a collaborative strategy, utilized efficient supply chains and leveraged each other's expertise and resources to enhance customer satisfaction. This approach has been made possible by technological advancements. The literature review identifies two research gaps: insufficient consideration of inherent uncertainty in construction projects and inade-quate attention to the multi-objective and multimodal nature of construction project models. To address uncertainties in construction projects, this study employed the Chance-Constrained Programming approach. Uncertainty-related parame-ters were identified and integrated into an optimization model. The primary objective of this study is to minimize project implementation delays. To achieve this, we employ exact algorithms for small and medium-scale problems and utilize NSGAII for large-scale scenarios. Our research emphasizes the critical importance of efficient project timing, cost optimi-zation, and proactive delay management for achieving successful project outcomes. The study reveals critical insights into the impact of resource allocation on the first objective function. The findings show 20% increase in resources for the first activity (i) raises the objective function to 310 units, while a 30% reduction in activity i's completion time lowers it to 188 units. These findings offer valuable benchmarks for decision-making and project optimization. Managers can use these insights to enhance decision-making, optimize resource allocation, and ensure timely project completion while maintaining quality and cost control.
Reza Ehtesham Rasi
Abstract
Scheduling is one of the key parameters to maintain competitive advantage of organizations, and can directly affect productivity, reduce production time and increase the profitability of an organization. Job shop scheduling problem (JSSP) seeks to find the optimal sequence of performing various jobs ...
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Scheduling is one of the key parameters to maintain competitive advantage of organizations, and can directly affect productivity, reduce production time and increase the profitability of an organization. Job shop scheduling problem (JSSP) seeks to find the optimal sequence of performing various jobs related to group of machines. The purpose of this paper is to provide a multi objective to optimize makespan, energy consumption and machine erosion in flexible JSSP. The problem of this paper is to assign each operation to a machine and to order the operations on the machines, such that the maximal completion time (makespan) of all operations is minimized. The obtained model belongs to NP-Hard class of optimization problems. In terms of overcoming NP-hardness of the proposed model and solve the complicated problem, a non-dominated sorting genetic algorithm (NSGAII) is employed. As there is no benchmark available in the literature, the non-dominated ranking genetic algorithm (NRGA) is developed to validate the results obtained and test problems are provided to show the applicability of the proposed methodology and evaluate the performance of the algorithms. In this study, to evaluate the performance of these algorithms, they were statistically analyzed using T-test. Ultimately, results of the selected model were ranked by applying the technique for order of preference by similarity to ideal solution (TOPSIS).
Somayeh Najafi-Ghobadi; Mahtab Sherafati
Abstract
Nowadays, supply chains have been facing significant economic forfeitures because of unpredicted disruptions. Furthermore, managers try to design sustainable and reliable supply chains. In this paper, we present an inventory-location model to propound a reliable three echelon supply chain which includes ...
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Nowadays, supply chains have been facing significant economic forfeitures because of unpredicted disruptions. Furthermore, managers try to design sustainable and reliable supply chains. In this paper, we present an inventory-location model to propound a reliable three echelon supply chain which includes a production plant, distribution centers, and retailers. The production plant distributes a single product to retailers through distribution centers that are at risk of disruption. We considered reactive (consider backup distribution center for each retailer) and proactive (distribution center fortification) activates to enhance the supply chain's reliability. The proposed model indicates the location of distribution centers (DCs), the DCs that must be fortified, the allocation of retailers to DCs, and the inventory policy of DCs. The problem is formulated as a nonlinear integer programming model. Since our model is an NP-hard problem, we provide a Lagrangian relaxation algorithm to solve it. Numerical examples demonstrate the computational efficiency of the proposed solution algorithm. Results show that, with increasing the budget of fortification, the total expected cost will decrease. A higher inventory cost leads to an increase in the number of opened DCs, while higher ordering cost and the transportation cost from production plant to DCs decrease the number of opened DCs. Among other results, the number of opened DCs is positively affected by the cost of transporting from DCs to retailers.
Mohammad Hossein Sadat Hosseini Khajouei; Nazanin Pilevari; Reza Radfar; Ali Mohtashami
Abstract
In recent decades, researchers are turning to the potential of ABMs to study complex phenomena. Due to intrinsic interconnections, structural interactions and inter-dependencies, individual variations, and communications of various components, supply chain network should be accordingly treated as a complex ...
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In recent decades, researchers are turning to the potential of ABMs to study complex phenomena. Due to intrinsic interconnections, structural interactions and inter-dependencies, individual variations, and communications of various components, supply chain network should be accordingly treated as a complex adaptive system. ABM is dominant tool exploring the emergent behavior of supply chain network with numerous interactive agents. This paper aims to conduct a systematic literature review on the agent-based modeling in the concepts of supply chain and various fields of research. Using reputable databases, combining intended keywords and applying filters based on restrictions and indicators, a total of 123 relevant articles are selected from the valid journals and conferences in year 2010-2019, and 17 subjects in association with supply chain management and 23 subjects related to other fields are presented. Moreover, a brief history and the definition of the three basic areas including complex systems, complex adaptive system and agent-based modeling are provided. The main objective is to provide a perspective based on agent-based modeling and complex adaptive systems for researchers in different sciences and especially supply chain researchers, who are not sufficiently familiar with the philosophy and applications of these approaches.
Mansooreh Iravani; Reza Bashirzadeh; M. J. Tarokh
Abstract
This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability ...
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This paper introduces a Travel Demand Management (TDM) model in order to decrease the transportation externalities by affecting on passengers’travel choices. Thus, a bi-objective bi-modal optimization model for road pricing is developed aiming to enhance environmental and social sustainability by considering to minimize the air pollution and maximize the social welfare as its objectives. This model determines optimal prices (bus fare and car toll) and optimal bus frequency simultaneously in an integrated model. The model is based on discrete choice theory and consideres the modes’ utility functions in its formulation. The proposed model is solved by two meta-heuristic methods (Non-dominated Sorting Genetic Algorithm-II (NSGA-II), Multi-Objectives Harmony Search (MOHS)) and the numerical results of a case study in Tehran are presented. The main managerial insights resulted from this case study is that its results support the idea of “free public transportation” or subsidizing the public transport as an effective way to decrease the transport related air pollution
Abolfazl Babazadeh Rafiei; Majid Motamedi; Sohrabi Tahmoores; Mohammad Hossein Darvish Motevalli
Abstract
Supply chain risk management is a preventive approach to risk management in the supply chain to avoid possible unex-pected consequences and to manage the blood supply chain (BSC) and achieve the maximum effectiveness and efficiency of this chain, risk management of the BSC is inevitable. This research ...
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Supply chain risk management is a preventive approach to risk management in the supply chain to avoid possible unex-pected consequences and to manage the blood supply chain (BSC) and achieve the maximum effectiveness and efficiency of this chain, risk management of the BSC is inevitable. This research aims to propose a mathematical model to reduce the risk of the BSC in the conditions of the COVID-19 pandemic. One of the most important contributions of this research is to consider the uncertainty in the demand parameter in the conditions of the COVID-19 pandemic and to provide a ro-bust planning model to overcome it in order to properly manage and control its risks. For this purpose, in this research a scenario-based multi-objective model is proposed with the aim of reducing the risk of the BSC in the conditions of the COVID-19 pandemic. In order to test the model, the problem is investigated in different sizes and using actual data and the results are presented, and sensitivity analysis is carried out on the changes in the parameters. Baron solver in GAMS 24.9 software is used to solve the proposed mathematical model. The proposed model determines the product sent from the blood center to the hospital, the amount of product produced in the blood center, the amount of blood collected from donors, the number of collection centers, the amount of blood stock in the blood center and hospital with the aim of reduc-ing cost and risk and increasing reliability. In this research, a scenario-based non-linear integer multi-objective model is proposed considering the level of supply and with the aim of reducing the risk of the BSC by reducing the cost and in-creasing the reliability of the BSC in the conditions of the COVID-19 pandemic, which can be used for risk management of the BSC in critical conditions of blood supply, such as the COVID-19 pandemic. Finally, to measure the sensitivity of the presented model performance to the change in the parameters, the sensitivity analysis on the behavior of the model in terms of the change in the shortage cost, the number of blood collection facilities and the objective functions is presented. The sensitivity analysis on the shortage cost parameter showed that with the increase in the shortage cost, the shortage rate decreased and this leads to an increase in the total cost.
Raheleh Moazami Goodarzi; Fardin Ahmadizar; Hiwa Farughi
Abstract
In this paper, a new model for hybrid flow shop scheduling is presented in which after the production is completed, each job is held in the warehouse until it is sent by the vehicle. Jobs are charged according to the storage time in the warehouse. Then they are delivered to customers by means of routing ...
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In this paper, a new model for hybrid flow shop scheduling is presented in which after the production is completed, each job is held in the warehouse until it is sent by the vehicle. Jobs are charged according to the storage time in the warehouse. Then they are delivered to customers by means of routing vehicles with limited and equal capacities. The problem’s goal is finding an integrated schedule that minimizes the total costs, including transportation, holding, and tardiness costs. At first, a mixed-integer linear programming (MILP) model is presented for this problem. Due to the fact that the problem is NP-hard, a hybrid metaheuristic algorithm based on PSO algorithm and GA algorithm is suggested to solve the large-size instances. In this algorithm, genetic algorithm operators are used to update the particle swarm positions. The algorithm represents the initial solution by using dispatching rules. Also, some lemma and characteristics of the optimal solution are extracted as the dominance rules and are integrated with the proposed algorithm. Numerical studies with random problems have been performed to evaluate the effectiveness and efficiency of the suggested algorithm. According to the computational results, the algorithm performs well for large-scale instances and can generate relatively good solutions for the sample of investigated problems. On average, PGR performs better than the other three algorithms with an average of 0.883. To significantly evaluate the differences between the algorithms’ solutions, statistical paired sample t-tests have been performed, and the results have been described for the paired algorithms.
Ahmad Jafarnejad; Ghahreman Abdoli; Hannan Amoozad Mahdiraji; Saber Khalili Esbouei
Abstract
In recent years, the relationship between the concepts of operations management and finance management has been an attractive area of research among researchers. One of the emerging areas at the beginning of the 21st century in the literature of operations and supply chain management is the topic of ...
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In recent years, the relationship between the concepts of operations management and finance management has been an attractive area of research among researchers. One of the emerging areas at the beginning of the 21st century in the literature of operations and supply chain management is the topic of supply chain finance (SCF). SCF is a new concept that provides efficient financing of the supply chain, where all parties can balance the working capital and improve cash flow at a reduced cost by utilizing the buyer's or other parties' credit rating. Hence, in this study, an approach to optimize financing based on the Stackelberg model in a three-level supply chain, considering the circumstances in which the supplier is financially constrained for fulfillment the buyer's order and funded by the bank as another member of the supply chain based on the purchase order financing (POF) is discussed. For this purpose, a nonlinear mathematical programming model has been developed to maximize the payoff function of the partners.
Sepideh Rahmani; Farzad Movahedi Sobhani; Hamed Kazemipoor; Majid Sheikh Mohammadi
Abstract
In order to survive and succeed in today's ever-changing business world, both established organizations and startups must be able to adapt and innovate. A key factor in this is the concept of open innovation, which has revolutionized how organizations acquire knowledge by facilitating collaboration and ...
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In order to survive and succeed in today's ever-changing business world, both established organizations and startups must be able to adapt and innovate. A key factor in this is the concept of open innovation, which has revolutionized how organizations acquire knowledge by facilitating collaboration and interaction between different entities. For startups, who are new players in the market, it is crucial to remain constantly vigilant and adaptable in order to thrive. The lean startup methodology has gained popularity as a means to efficiently develop products and businesses. Investment plays a crucial role in the sustainability and growth of startups, and investors assess various factors when making investment decisions. However, previous studies have often analyzed these factors statically, without considering their dynamic interactions over time. This paper aims to explore the dynamics of startup ecosystems and the factors influencing investment deci-sions. It adopts a qualitative research approach, using expert opinions and existing literature to identify and analyze causal loops that impact the willingness to invest in startups. The study constructs a dynamic model that illustrates the relationships and feedback mechanisms among different variables, including learning, synergy, economic factors, financial risk, and startup value. The model reveals that multiple variables influence the willingness to invest, and their interactions create a complex dynamic system. Through scenario analyses, the paper suggests strategies to enhance investment readi-ness and attract investors. These scenarios include increasing cooperation to foster synergy, improving startup value through innovation and efficiency, and managing economic factors and financial risks. Sensitivity analysis demonstrates how changes in variables like cooperation can impact the willingness to invest. The research underscores the importance of understanding the interplay of these factors in a dynamic ecosystem to make informed investment decisions and foster startup success.
Masoud Rabbani; Amin Abazari; Hamed Farrokhi-Asl
Abstract
Using second-generation biomass and biofuel deal with environmental pollution and CO2 emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO2 ...
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Using second-generation biomass and biofuel deal with environmental pollution and CO2 emissions. Therefore, this paper design an integrated multi-period bi-objective biofuel supply chain network using support vector machine (SVM) and economic analysis to reduce the cost of generating biofuels and CO2 emissions. The economic analysis consists of three scenarios for supplying biomass. The SVM method specifies the potential place to build the bio-refinery. The next step solves the model with the augmented ε-constraint method. Finally, results show that biomass production and imports simultaneously reduce costs by 24.5% compared to the production scenario and 4.3% compared to the import scenario. According to the results obtained, despite the increase in cost, it reduces the amount of CO2 emissions. So, the Pareto solution resulted from the augmented ε-constraint method for the problem is determined as one of the most effective techniques to help the decision-makers.