M. Johari; S.M. Hosseini Motlagh; M.R. Nematollahi
Volume 3, Issue 2 , December 2016, , Pages 58-87
Abstract
In this paper, the coordination of pricing and periodic review inventory decisions in a supplier-retailer supply chain (SC) is proposed. In the investigated SC, the retailer faces a stochastic price dependent demand and determines the review period, order-up-to-level, and retail price. On the other hand, ...
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In this paper, the coordination of pricing and periodic review inventory decisions in a supplier-retailer supply chain (SC) is proposed. In the investigated SC, the retailer faces a stochastic price dependent demand and determines the review period, order-up-to-level, and retail price. On the other hand, the supplier decides on the replenishment multiplier. Firstly, the decentralized and centralized decision making models are established. Afterwards, a quantity discount contract as an incentive scheme is developed to coordinate the pricing and periodic review replenishment decisions simultaneously. The minimum and maximum discount factors, which are acceptable to both SC members, are determined. In addition, a set of numerical examples is conducted to demonstrate the performance of the proposed coordination model. The results demonstrate that the proposed coordination mechanism can improve the profitability of SC along with both the SC members in comparison with the decentralized model. In addition, the results revealed that the proposed incentive scheme is able to achieve channel coordination. Moreover, the coordination model can fairly share the surplus profits between SC members based on their bargaining power.
Amir Hossein Hosseinian; Vahid Bardaran
Abstract
In this research, we study the multi-skill resource-constrained project scheduling problem, where there are generalized precedence relations between project activities. Workforces are able to perform one or several skills, and their efficiency improves by repeating their skills. For this problem, a mathematical ...
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In this research, we study the multi-skill resource-constrained project scheduling problem, where there are generalized precedence relations between project activities. Workforces are able to perform one or several skills, and their efficiency improves by repeating their skills. For this problem, a mathematical formulation has been proposed that aims to optimize project completion time, reworking risks of activities, and costs of processing the activities, simultaneously. A modified version of the Pareto Archived Evolution Strategy (MV-PAES) is developed to solve the problem. Contrary to the basic PAES, this algorithm operates based on a population of solutions. For the proposed method, we devised crossover and mutation operators, which strengthen this algorithm in exploring solution space. Comprehensive numerical tests have been conducted to evaluate the performance of the MV-PAES in comparison with two other meta-heuristics. The outputs show the excellence of the MV-PAES in comparison with other methods. A real-world software development project has been studied to demonstrate the practicality of the proposed model for real-world environment. The influence of competency evolution has been investigated in this case study. The results imply that the competency evolution has a considerable impact on the objective function values.
E. Babaee Tirkolaee; M. Alinaghian; M. Bakhshi Sasi; M. M. Seyyed Esfahani
Volume 3, Issue 1 , June 2016, , Pages 61-76
Abstract
The urban waste collection is one of the major municipal activities that involves large expenditures and difficult operational problems. Also, waste collection and disposal have high expenses such as investment cost (i.e. vehicles fleet) and high operational cost (i.e. fuel, maintenance). In fact, making ...
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The urban waste collection is one of the major municipal activities that involves large expenditures and difficult operational problems. Also, waste collection and disposal have high expenses such as investment cost (i.e. vehicles fleet) and high operational cost (i.e. fuel, maintenance). In fact, making slight improvements in this issue lead to a huge saving in municipal consumption. Some incidents such as altering the pattern of waste collection and abrupt occurrence of events can cause uncertainty in the precise amount of waste easily and consequently, data uncertainty arises. In this paper, a novel mathematical model is developed for robust capacitated arc routing problem (CARP). The objective function of the proposed model aims to minimize the traversed distance according to the demand uncertainty of the edges. To solve the problem, a hybrid metaheuristic algorithm is developed based on a simulated annealing algorithm and a heuristic algorithm. Moreover, the results obtained from the proposed algorithm are compared with the results of exact method in order to evaluate the algorithm efficiency. The results have shown that the performance of the proposed hybrid metaheuristic is acceptable.
Mohammad Ehsanifar; Nima Hamta; Fariba EsmaeilZadeh
Abstract
This paper identified and ranked the lean product factors effecting economic function of production companies in Mazandaran province. 24 sub-factors and five main factors were categorized including supplier management, purchase and provision system, human resource organization, organizing, leadership, ...
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This paper identified and ranked the lean product factors effecting economic function of production companies in Mazandaran province. 24 sub-factors and five main factors were categorized including supplier management, purchase and provision system, human resource organization, organizing, leadership, and IT. The findings of the paper show that the factor of supplier management is the most influential factor in economic function of production companies and IT has the least effect on the economic function of production companies.
Saeid Emamgholizadeh; Ahmad Jafarzadeh Afshari; Maryam Shabani Bahmand
Abstract
Organizations have found that functional approach to business destroys flexibility and agility by gaining experience over the time. The main weakness with Task-based organizations is that they can hardly act flexibly and adapt themselves to the changing environment. In today’s' dynamic and competitive ...
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Organizations have found that functional approach to business destroys flexibility and agility by gaining experience over the time. The main weakness with Task-based organizations is that they can hardly act flexibly and adapt themselves to the changing environment. In today’s' dynamic and competitive business world, organizations focus significantly on managing and improving their business processes. Therefore, nowadays to be survived and successful, certainly, the process approach must be followed. In addition, organizations having such improvement and innovations are looking to create organizational wealth. In this regard, the present study is trying to identify and describe processes from reputable reference models in Customer Relationship Management (CRM) and more importantly to design and streamline CRM processes effectively for organizations in order to improve processes and offer value to customers. In this paper, first, by identifying and explaining CRM reference models, three models were selected based on five criteria (flexibility, Understandability, comprehensiveness, Completeness, and Usability) using Analytic Hierarchy Process (AHP) technique which is relative as follow: SAP, CCOR & PCF. Then, the processes of the three models were extracted and gathered in a comprehensive list to offer a united framework to design CRM processes. Finally, a case study will show the applicability of the proposed model. With this paper, we enrich research by a valuable process framework for developing well-designed reference models.
Ali Eslamibidkoli; Mohammad Reza Sadeghi Moghadam; Tahmurath Hasangholipour
Volume 10, Issue 1 , July 2023, , Pages 67-76
Abstract
Emerging companies or start-ups are growing rapidly and their number is increasing every day so that the number of knowledge-based and start-up companies in Iran has increased from about 55 companies in 2013 to more than 5965 companies in 2021. The capital element is the main and most productive factor ...
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Emerging companies or start-ups are growing rapidly and their number is increasing every day so that the number of knowledge-based and start-up companies in Iran has increased from about 55 companies in 2013 to more than 5965 companies in 2021. The capital element is the main and most productive factor for the success of start-ups and choosing the right financing method to achieve success is inevitable. The start-up literature offers a number of ways to finance entrepreneurs that are often presented in other geographies (often in startups operating in the United States) and those models cannot be accepted as non-native. Developing a strategic local financing framework based on the tacit knowledge gained by emerging digital startups can address this issue. Based on this, the present study aims to fill the existing gaps by designing a strategic financing framework for digital start-ups based on local criteria in order to be effective in the success of digital start-ups. The statistical population of the quality sector includes entrepreneurs and digital business owners, 30 of whom were identified by snowball method and interviewed in a semi-authorized manner. The statistical population of the quantitative section includes 166 digital businesses operating in Tehran science and technology parks that have been selected using Cochran's formula in a simple random method. To collect data, the method of library review and interviews with experts and finally the distribution of questionnaires have been used. The analysis of the findings in the qualitative stage was performed with a thematic analysis approach and the results showed that 101 open codes were categorized in 17 sub-themes and 17 sub-themes were placed in 5 main themes. In the quantitative stage, confirmatory factor analysis and structural equation modeling with LISREL software were used. The results showed that five main factors including corporate factors, macro environmental factors, investment factors, business valuation factors and idea and product factors are effective in designing digital business financing strategy.
Shahla Rowshandel; Ali Asghar Anvary Rostamy; Iraj Noravesh; Roya Darabi
Abstract
Prediction of stock returns has always been one of the most important issues in finance. Investors have attracted to use of Fama-French Five-Factor Model (FFFFM) as one of the powerful methods for pricing financial assets and predicting the stock returns. This research investigates the predictability ...
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Prediction of stock returns has always been one of the most important issues in finance. Investors have attracted to use of Fama-French Five-Factor Model (FFFFM) as one of the powerful methods for pricing financial assets and predicting the stock returns. This research investigates the predictability of stock returns by including some important firms features namely cash holdings, dividend rate, and free cash flow to equity to FFFFM. Statistical samples consist of 75 companies listed on the Tehran Stock Exchange (TSE) during 2003-2017. The results of panel data test indicate positive significant effects of all variables in FFFFM (i.e. book to market value ratio, company size, growth opportunity, profitability, and investment) as well as newly added firms feature variables (cash holding, dividend rate, and free cash flow to equity). However, the investment has a negative impact on the returns due to the initial estimate of primary FFFFM. In addition, the results indicate that the inclusion of firms feature variables significantly improve the predictive power of stock returns. Finally, by comparing the predictive power of the models, the best prediction model is determined.
Zahra Shams Esfandabadi; Mir Mehdi Seyyed Esfahani
Abstract
Automobile hull insurance has attracted much attention due to the high rate of vehicle applications in daily lives. Since purchasing these policies is optional in Iran and their premium rates are set competitively, a competition is formed among the insurance companies for attracting low risk drivers. ...
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Automobile hull insurance has attracted much attention due to the high rate of vehicle applications in daily lives. Since purchasing these policies is optional in Iran and their premium rates are set competitively, a competition is formed among the insurance companies for attracting low risk drivers. However, most of the insurers still use comparative rates and pay no or less attention to the factors affecting risk in premium calculations. Considering the importance of fair ratemaking in attracting and maintaining good risks and encouraging bad risks to repent or leave the portfolio, and taking into account the shortcomings of the available databases, this paper focuses on determining and classifying the risk factors affecting premium calculation in automobile hull insurance from the viewpoint of the experts. In this regard, Fuzzy Delphi method is utilized, the factors are classified and the efficiency of the classification is checked by using Confirmatory Factor Analysis (CFA).
H. Mokhtari
Volume 2, Issue 2 , December 2015, , Pages 55-82
Abstract
In today’s competitive market place, companies seek an efficient structure of supply chain so as to provide customers with highest value and achieve competitive advantage. This requires a broader perspective than just the borders of an individual company during a supply chain. This paper investigates ...
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In today’s competitive market place, companies seek an efficient structure of supply chain so as to provide customers with highest value and achieve competitive advantage. This requires a broader perspective than just the borders of an individual company during a supply chain. This paper investigates an aggregate production planning problem integrated with distribution issues in a supply chain so as to simultaneously optimize characteristics of these supply chain drivers. The main contribution of this paper is to consider the aggregate production-distribution planning (APDP) problem jointly with multiple stage, multiple product, and multiple vehicle. Moreover, we considered both routing and direct shipment as transportation system which is not considered in APDP literature so far. A mixed-integer linear programming formulation is suggested for two distinct Scenarios: (i) when we have direct shipment in which all shipments are transported directly from manufacturer to customers, and (ii) when we have routing option in which the vehicles can move through routes to deliver products to more than one customer at a trip. A numerical analysis is performed to compare performance of problem in two above Scenarios. Moreover, to assess applicability of problem, some computational experiments are implemented on small, medium and large sized problems.
M. Mahmoudinezhad; M. Ghoreishi; A. Mirzazadeh; A. Ghodratnama
Volume 1, Issue 1 , November 2014, , Pages 58-71
Abstract
In this paper, Economic Order Quantity ( ) based model for non-instantaneous deteriorating items with imperfect quality, permissible delay in payments and inflation is proposed. We adopt a time-dependent demand function. Also, the effects of time value of money are studied using the Discounted Cash Flow ...
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In this paper, Economic Order Quantity ( ) based model for non-instantaneous deteriorating items with imperfect quality, permissible delay in payments and inflation is proposed. We adopt a time-dependent demand function. Also, the effects of time value of money are studied using the Discounted Cash Flow approach. Moreover, we assume that orders may contain a random proportion of defective items, which follow a known distribution and an inspection process is utilized to describe the defective proportion of the received lot. The mathematical model have been derived for obtaining the optimal number of cycle and the optimal inspection time so that the present value of total cost in a finite time horizon is minimized. An algorithm has been presented to find the optimal solution. Finally, numerical examples are provided to illustrate the solution procedure.
A. Ayooq; A. Alem Tabriz; A. Javani
Volume 2, Issue 1 , June 2015, , Pages 61-73
Abstract
In this paper, a new mathematical model for the problem of job scheduling in virtual manufacturing cells (VMC) is presented to minimizing the completion time of all jobs. Sequence dependent setup times of machines is considered and lot-streaming is possible. In Virtual manufacturing cells, ...
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In this paper, a new mathematical model for the problem of job scheduling in virtual manufacturing cells (VMC) is presented to minimizing the completion time of all jobs. Sequence dependent setup times of machines is considered and lot-streaming is possible. In Virtual manufacturing cells, each job has a different processing path and there is a set of machines for processing each operation. There are multiple machine types with several identical machines in each type locating in different locations in the shop floor. In this type of system, the cells are not physical and Machines can be shared between the cells. In Mixed-integer nonlinear programming model presented, the scheduling decisions involve assigning a machine to each operation, the start time at each operation, the start time of machines and sub-lot sizes of each job. Some test problems have been generated to demonstrate the implementation of the model and solved by Lingo.
Seyyed Akbar Gholamian
Abstract
Railway scheduling is a complex task of rail operators that involves the generation of a conflict-free train timetable. This paper presents a discrete-event simulation-based optimization approach for solving the train timetabling problem to minimize total weighted unplanned stop time in a hybrid single ...
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Railway scheduling is a complex task of rail operators that involves the generation of a conflict-free train timetable. This paper presents a discrete-event simulation-based optimization approach for solving the train timetabling problem to minimize total weighted unplanned stop time in a hybrid single and double track railway networks. The designed simulation model is used as a platform for generating feasible conflict-free train timetables. It includes detailed infrastructure information, such as station characteristics, trains running time and praying intervals. The proposed approach has the capability of scheduling trains in large-scale networks subject to the capacity constraints and infrastructure characteristics. In optimization procedure, a path relinking meta-heuristic algorithm is utilized to generate near-optimal train timetables. A case study of Iran railway network is selected for examining the efficiency of the meta-heuristic algorithm. The computational result shows that the proposed approach has the capability of generating near-optimal timetable in real-sized train scheduling problems.
Fatemeh Amirbeygi; Seyyed Hosein Seyyed Esfahani; Behrooz Khorshidvand
Abstract
Environmental pollution and the deterioration of natural resources are now considered significant challenges in human societies. In fact, environmental pollution is mainly caused by manufacturing industries. Most industries (e.g., the cement industry) employ the green supply chain to overcome ecological ...
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Environmental pollution and the deterioration of natural resources are now considered significant challenges in human societies. In fact, environmental pollution is mainly caused by manufacturing industries. Most industries (e.g., the cement industry) employ the green supply chain to overcome ecological problems, a goal that requires various techniques for quantifying the environmental impacts on the supply chain to improve processes. This study aimed to evaluate the green supply chain performance at 11 cement manufacturing factories through the hybrid BSC–DEA approach within the 2018–2020 period. After the principal indices were identified and placed in each perspective of the balanced scorecard (BSC), the DEMATEL technique was adopted to determine the relationships of perspectives. The multistage data envelopment analysis (DEA) model was then employed to measure the efficiency of each BSC perspective and the total network efficiency. Finally, reference units were introduced to improve the inefficient units. According to the results, managers focus mainly on the financial section and customers but pay less attention to growth and learning. The organization yielded the best efficiency in 2020 by following an upward trend. The energy consumption rate, clinker–cement ratio, and CO2 emission rate were analyzed in this study to better investigate the environmental problems in the cement industry. Most of the units followed upward trends in both CO2 emission and energy consumption but experienced a downward trend in clinker production.
Maryam Shams; Ahmad Jafarzadeh Afshari; Amir Khakbaz
Abstract
Cloud computing is considered to be a new service provider technology for users and businesses. However, the cloud environment is facing a number of challenges. Resource allocation in a way that is optimum for users and cloud providers is difficult because of lack of data sharing between them. On the ...
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Cloud computing is considered to be a new service provider technology for users and businesses. However, the cloud environment is facing a number of challenges. Resource allocation in a way that is optimum for users and cloud providers is difficult because of lack of data sharing between them. On the other hand, job scheduling is a basic issue and at the same time a big challenge in reaching high efficiency in the cloud computing environment. In this paper, “the cloud resources management problem” is investigated that includes allocation and scheduling of computing resources, such that providers achieve the high efficiency of resources and users receive their needed applications in an efficient manner and with minimum cost. For this purpose, a group technology based non-linear mathematical model is presented with an aim at minimization of load difference of servers, number of transfers between servers, number of active virtual machines, maximum construction time, the cost of performing jobs and active servers energy consumption. To solve the model, a meta-heuristic multi-objective hybrid Genetic and Particle Swarm Optimization algorithm is proposed for resource allocation and scheduling. In order to demonstrate the validity and efficiency of the algorithm, a number of problems with different dimensions are randomly created and accordingly the efficiency and convergence capability of the suggested algorithm is investigated. The results indicated that the proposed hybrid method has had an acceptable performance in generating high quality, diverse and sparse solutions.
F. Molavi; E. Rezaee Nik
Volume 3, Issue 1 , June 2016, , Pages 77-88
Abstract
Resource limitation in zero time may cause to some profitable projects not to be selected in project selection problem, thus simultaneous project portfolio selection and scheduling problem has received significant attention. In this study, budget, investment costs and earnings are considered to be stochastic. ...
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Resource limitation in zero time may cause to some profitable projects not to be selected in project selection problem, thus simultaneous project portfolio selection and scheduling problem has received significant attention. In this study, budget, investment costs and earnings are considered to be stochastic. The objectives are maximizing net present values of selected projects and minimizing variance of them. Benefiting an efficient multi-objective approach to satisfy every conflicting objective, an integer non-linear goal programming model is developed. Another contribution of this paper is to consider cost dependency between the projects, in project portfolio selection and scheduling problem. Due to the complexity of this problem, especially in large sizes, imperialist competitive algorithm and genetic algorithm are presented. The effectiveness of the model and proposed algorithms are demonstrated via a case study in a knowledge based company at Ferdowsi University of Mashhad. The result shows high performance of the both proposed algorithms.
Shaaban ALI Hoseinpour; Behrouz Afshar Nadjafi; Seyed Taghi Akhavan Niaki
Volume 10, Issue 1 , July 2023, , Pages 77-87
Abstract
The firefighter problem on a graph, depending on the environment, the graph can be continuous or discrete, which includes tree, cubic, regular and irregular graphs, etc., is described in such a way that by starting a fire from a series of vertices, the goal is to contain the fire with the maximum number ...
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The firefighter problem on a graph, depending on the environment, the graph can be continuous or discrete, which includes tree, cubic, regular and irregular graphs, etc., is described in such a way that by starting a fire from a series of vertices, the goal is to contain the fire with the maximum number of vertices saved. Our main innovation is to model the firefighter problem with on a bi- objective model, which simultaneously saves the maximum number of vertices with the minimum number of firefighters. The firefighter problem is a type of Np-hard problem, and because we defined the problem as a bi-objective problem and added three constraints to it, the problem became more difficult, and the weighted bi-objective model is also Np-hard. To solve the NP-hard problem, we used multi-objective optimization4 such as Goal Programming (GP), ε- Constraint, Global Criterion Approach, Weighting Sum Method methods. To prove the performance of our method, we used a randomly generated sample.
Hadi Nasseri; Abdollah Baghban; Iraj Mahdavi
Abstract
This paper describes an application of fuzzy multi-objective quadratic model with flexible constraints for optimal allocation of limited available water resources among different water-user sectors. Due to the fact that, water resource allocation problem is one of the practical and essential subjects ...
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This paper describes an application of fuzzy multi-objective quadratic model with flexible constraints for optimal allocation of limited available water resources among different water-user sectors. Due to the fact that, water resource allocation problem is one of the practical and essential subjects in real world and many of the parameters may be faced by uncertainty. In this paper, we present α - cut approach for transforming fuzzy multi-objective quadratic programming model with flexible constraints into a crisp form. By using this approach a multi-parametric multi-objective programming model corresponding to α and parameters of flexible constraints is obtained. One of the advantages of this model is that the α - cut level is not determined by the decision makers. Actually, this model itself can calculate the α - cut level. In order to achieve a desired Pareto optimal value of multi-parametric multi-objective model, we use goal programming method for illustration of water resource allocation with sensitivity analysis of lower bound of parameters in flexible constraints. To illustrate the efficiency of the proposed approach, we apply it for a real case problem of water resource allocation.
Mojtaba Arab Momeni; Saeed Yaghoubi; Mohammad Reza Mohammad Aliha
Abstract
In this paper, an inventory model for deterioration items in a two-echelon supply chain including one retailer and one manufacturer is proposed by considering the stock and price dependent demand and capacity constraint for holding inventories. First, the model is presented as a leader-follower game ...
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In this paper, an inventory model for deterioration items in a two-echelon supply chain including one retailer and one manufacturer is proposed by considering the stock and price dependent demand and capacity constraint for holding inventories. First, the model is presented as a leader-follower game in which the manufacturer announces wholesale prices. Second, the retailer decides for the order quantity and price of the items based on the wholesale prices. Then, by introducing the integrated model of the supply chain, a cost-sharing contract is applied to coordinate the manufacturer and the retailer. On the other hand, by using the convergence properties of the model and proving non-concavity of the problem, a meta-heuristic algorithm, namely iterative local search (ILS) is proposed to solve the models. The results show the determinant role of the capacity constraint on the optimal decisions and the ability of the proposed contract to coordinate the supply chain. Moreover, it is shown that the proposed algorithm outperforms the well-known interior point algorithm as the results of the initiations embedded in it for the special problem.
Amir Albadvi; Hossein Hashemi; Mohammad Reza Amin-Naseri; Babak Teimourpour
Abstract
Reliability is a fundamental factor in the operation of bus transportation systems for the reason that it signifies a straight indicator of the quality of service and operator’s costs. Todays, the application of GPS technology in bus systems provides big data availability, though it brings the ...
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Reliability is a fundamental factor in the operation of bus transportation systems for the reason that it signifies a straight indicator of the quality of service and operator’s costs. Todays, the application of GPS technology in bus systems provides big data availability, though it brings the difficulties of data preprocessing in a methodical approach. In this study, the principal component analysis is utilized to systematically assess the reliability indicators based on automatic vehicle location (AVL) data. In addition, the significant reliability indicators affecting the bus reliability are identified using a statistical analysis framework. The proposed bus reliability assessment framework can be applied to each bus route or a complete network. The proposed methodology has been validated using computational experiments on real-world AVL datasets extracted from the bus system in Qazvin, Iran. The analysis indicates that 1) on-time performance, 2) headway regularity, 3) standard deviation of the travel time of the buses, and 4) 50th percentile travel time are key indicators the reliability of bus services. The potential of the proposed methodology is discussed to provide insights for bus operators. Using the proposed approach in the article, the desirable reliability status of bus lines is identifiable from the point of view of key stakeholders, and the ways to improve reliability can be more clearly defined.
Arman Sajedinejad; Erfan Hassannayebi; Mohammad Saviz Asadi Lari
Abstract
It is scientifically challenging to determine the inventory level all through the supply chain in such a way that the desired objectives such as effectiveness and responsiveness of the supply chain system can be obtained. Simulation is a means for solving various problems which cannot be solved ...
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It is scientifically challenging to determine the inventory level all through the supply chain in such a way that the desired objectives such as effectiveness and responsiveness of the supply chain system can be obtained. Simulation is a means for solving various problems which cannot be solved by regular exact models such as mathematical ones due to their complexity. The present paper is aimed at simulating lean multi-product supply chain system as well as optimization of the objectives of supply chain. Variables of the simulation model include two types of Kanbans namely withdrawal, and production to determine the inventory level, and batch size of delivery parts for each stage of supply chain. So, in this paper simulation model was developed for supply chains, taking into consideration the different production scenarios and were modeled and compared. A production scenario is adopted for each level of the chain in order to achieve the objectives. The use of meta-heuristic techniques leads us to optimization of these variables which helps decrease delay of both product delivery and inventory level of supply chain. In this case, Genetic Algorithm has applied to find the best variable values of each scenario (included in the right number of each Kanbans), aimed at decreasing the costs and delivery delays. An example based on a case study is given to illustrate the efficiency of the proposed approach. Considering each level of supply chain, the ratio between and among cost, inventory, and delivery delay variables were obtained.
A. Yaghoubi; M. Asghari
Volume 3, Issue 2 , December 2016, , Pages 88-106
Abstract
In today’s competitive world, the need to supply chain management (SCM) is more than ever. Since the purpose of logistic problems is minimizing the costs of organization to create favorable time and place for the products, SCM seek to create competitive advantage for their organizations and increase ...
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In today’s competitive world, the need to supply chain management (SCM) is more than ever. Since the purpose of logistic problems is minimizing the costs of organization to create favorable time and place for the products, SCM seek to create competitive advantage for their organizations and increase their productivity. This paper proposes a new multi-objective model for integrated forward / reverse logistics network including three objective functions which belongs to the class of NP-hard problems. The first objective attempts to minimize the total cost of the supply chain network. The second objective attempts to maximize the customer service level (customer responsiveness) in both forward and reverse networks. The third objective tries to minimize the total number of defects of in raw material obtained from suppliers and thus increase the quality level. To solve the proposed model, the non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranked genetic algorithms (NRGA) are used. A Taguchi experimental design method was applied to set and estimate the proper values of GAs parameters for improving their performances. Besides, to evaluate the performance of the two algorithms some numerical examples are produced and analyzed with some metrics to determine which algorithm works better. In order to determine whether there is a significant difference between the performances of the algorithms, the one-way ANOVA and Tukey test are used at 0.95 confidence level. Finally, the performance of the algorithms is analyzed and the results are reported.
Amir Ebrahimzadeh Pilerood; Mehdi Heydari; Mohammad Mahdavi Mazdeh
Abstract
In this paper, the problem of two-machine flow shop scheduling to minimize total energy costs under time-of-use tariffs is investigated. As the objective function of this study is not a regular measure, allowing intentional idle-time can be advantageous. So this study considers two approaches, one for ...
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In this paper, the problem of two-machine flow shop scheduling to minimize total energy costs under time-of-use tariffs is investigated. As the objective function of this study is not a regular measure, allowing intentional idle-time can be advantageous. So this study considers two approaches, one for non-delay version of the problem and the other one for a situation when inserting intentional idle time is permitted. A mixed integer linear programming is formulated to determine the timing of jobs in order to minimize total energy costs while idle time insertion is allowed. For the non-delay version of the problem, a branch-and-bound algorithm is presented. A lower bound and several dominance properties are used to increase the speed of the branch-and-bound algorithm. Computational experiments are also given to evaluate the performance of the algorithm. Based on results, the proposed algorithms can optimally schedule jobs in small size samples but by increasing the number of jobs from 15 and cost periods from 3, the performance of branch-and-bound has been decreased.
Behrouz Khorshidvand; Ashkan Ayough; Akbar Alem Tabriz
Volume 1, Issue 1 , November 2014, , Pages 72-82
Abstract
In this article, two different systems subject to shocks occurring based on a non-homogeneous Poisson process (NHPP) are analyzed. Type –I system is consisted of a single unit and type –II system is consisted of two parallel units in which both units operate identically and simultaneously. ...
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In this article, two different systems subject to shocks occurring based on a non-homogeneous Poisson process (NHPP) are analyzed. Type –I system is consisted of a single unit and type –II system is consisted of two parallel units in which both units operate identically and simultaneously. In type –I system occurrence of a shock causes system stopping and consequently will be received minimal repairs. Also this system is replaced preventively at time Ψ, or at time less than Ψ due to probable failure. In type –II system a shock to each unit leads to unit stopping and accordingly the unit receives minimal repairs and another unit receives preventive maintenance services with no system stop. Simultaneously, this system is replaced at time Ψ or at times less than Ψ preventively, due to the failure of both units. Systems will be replaced with new and the same types when minimizes total expected cost.
Z. Arastia; T.H. Hejazi; Z. Geilari
Volume 2, Issue 1 , June 2015, , Pages 74-94
Abstract
Iranian bread production methods are often unsanitary, in the last decades, different attempts were made to mechanize production of Iranian breads, but a few of them, due to a variety of factors, could succeed. The aim of this study is to examine various factors affecting the system of bread production ...
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Iranian bread production methods are often unsanitary, in the last decades, different attempts were made to mechanize production of Iranian breads, but a few of them, due to a variety of factors, could succeed. The aim of this study is to examine various factors affecting the system of bread production in Iran and to provide effective solutions for the development of mechanized bakeries as the main strategy for improving the quality of bread production. Existence of different factors and the relation between them makes the system of bread production a complex system; therefore, this study uses system dynamics approach to analyze this system and to design solutions. Furthermore, the system of bread production is broken down to three subsystems: knowledge and technology subsystem, economic subsystem, and political and social subsystem.
S.H. Seyyed Esfahani; E. Asgharizadeh; GH. Abdoli; B. Dorri
Volume 2, Issue 2 , December 2015, , Pages 83-95
Abstract
Game theory is the study of mathematical models and cooperation between intelligent rational decision-makers. This paper provides a flexible model to calculate pay-off matrix based on several importance factors. This model is adapted by cooperative game and developed for some competitive advantages ...
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Game theory is the study of mathematical models and cooperation between intelligent rational decision-makers. This paper provides a flexible model to calculate pay-off matrix based on several importance factors. This model is adapted by cooperative game and developed for some competitive advantages sections in pharmaceutical industry. An optimum solution is derived by considering Nash equilibrium method for each section. Cooperative game extended for three players in a common market. Each player is looking for increase its market share with respect to participation of other competitors. Due to factors like capability of players to perform their strategic behaviors, market share adjustment by face to face comparison, the ability of any player in defined section and the importance of competitive advantage for players is basis of the calculation. A random example has been generated that the result of which led to achieve equilibrium market share for three players.