T.H. Hejazi; I. Soleimanmeigouni
Volume 1, Issue 1 , November 2014, , Pages 20-30
Abstract
Long-term planning is a challenging process for dealing with problems in big industries. Quick and flexible process of responding to the existing variable requirements are considered in such problems. Some of important strategic decisions which should be made in this field are, namely the way that manufacturing ...
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Long-term planning is a challenging process for dealing with problems in big industries. Quick and flexible process of responding to the existing variable requirements are considered in such problems. Some of important strategic decisions which should be made in this field are, namely the way that manufacturing facilities should be applied as well as assignment and design the system of delivery of orders. On the other hand, by using the small core and big network viewpoint in planning, such decisions should be made in a concentrated way. In this paper, a robust multi criteria group decision making model based on TOPSIS method is proposed, which evaluates the requirements of a real case study. In this regard, firstly important criteria in such environments would be determined. Secondly, using expert’s opinions and statistical analysis methods the group multi criteria decision making model would be constructed.
Pooyan Hajy Alikhani; Mohamad Reza Sadeghi Moghadam; Seyed Mostafa Razavi; Ali Mohaghar
Abstract
Retailers commonly offer discounts to encourage consumers to purchase more products thereby increasing retailers’ revenues. This article focuses on modeling the seller pricing decisions by using agent-based approach when the price, as a tool of revenue management, decreases. Considering the seller ...
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Retailers commonly offer discounts to encourage consumers to purchase more products thereby increasing retailers’ revenues. This article focuses on modeling the seller pricing decisions by using agent-based approach when the price, as a tool of revenue management, decreases. Considering the seller as an agent who uses price changes to maximize its total revenues, the objective of this research is to find the proper seller’s decision about the rate of discount on products in 3 different scenarios. In the first scenario, all products’ price elasticity of demand are the same and the products have relatively elastic demand. In the second scenario, all goods have the same price elasticity of demand and have relatively inelastic demands. The third scenario presents a combination of the first and the second scenarios in which the price elasticity of demand of products are different and goods with elastic and inelastic demand are placed next to each other. Also, all goods in each scenario are substitutes. In the first scenario, reducing the price causes the downward trend in rate of profit even though the discount could increase the revenue. In the second scenario, the agent behaves differently which offering the discount does not increase the revenue. In the third scenario, the products’ discount increases the revenue with a slope less than the first scenario. Also, the discount for all products doesn’t cause income growth. Therefore, some goods without any discount remain in shelf. Consequently, the proposed model in this research shows the proper rate of discount on each product in different product layouts.
Somaye Ramezani; Katayuon Naderi
Abstract
Today, in the existing competitive market, proper management of the supply chain has attracted a lot of attention to increasing profitability and customer satisfaction. Managers and decision-makers may use policies to survive in this situation, but a desirable outcome will only come when a precise and ...
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Today, in the existing competitive market, proper management of the supply chain has attracted a lot of attention to increasing profitability and customer satisfaction. Managers and decision-makers may use policies to survive in this situation, but a desirable outcome will only come when a precise and comprehensive model is used. Therefore, a detailed design and systematic planning of the supply chain seems necessary with all levels and units in order to increase the efficiency of the entire supply chain. In this research, two main objectives will be considered using multi-objective optimization methods. The first goal is to minimize the total cost of locating the warehouses in the supply chain, and the second goal is to maximize the level of customer satisfaction and service level of Bonny Chow Company. Computational results show the acceptable performance of the proposed method on a set of real-sized instances and demonstrate its efficiency in solving generated scenarios.
Ashkan Ayough
Abstract
Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature ...
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Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature of cost parameters. Considering the importance of coping with customer demand in different periods at different and variable rates, in this research, demand is considered fuzzy and the APP decisions modeled through a bi-objective LP model optimizing production and workforce level costs. The APP decisions are taken in two rounds, First The fuzzy model is transformed to a crisp goal programming counterpart and in the second round as the principal contribution of this paper, the APP decisions for rest of the horizon are updated based on actual demand occurred during starting periods. By generating several sample problems and using the Lingo, the validity of the proposed model is shown.
Ali Yaghoubi; M. Amiri
Volume 2, Issue 2 , December 2015, , Pages 26-42
Abstract
This paper presents a new multi-objective fuzzy stochastic data envelopment analysis model (MOFS-DEA) under mean chance constraints and common weights to estimate the efficiency of decision making units for future financial periods of them. In ...
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This paper presents a new multi-objective fuzzy stochastic data envelopment analysis model (MOFS-DEA) under mean chance constraints and common weights to estimate the efficiency of decision making units for future financial periods of them. In the initial MOFS-DEA model, the outputs and inputs are characterized by random triangular fuzzy variables with normal distribution, in which data are changing sequentially. Since the initial MOFS-DEA model is a complex model, we convert it to its equivalent one-objective stochastic programming by using infinite-norm approach. To solve it, we design a new hybrid meta-heuristic algorithm by integrating Imperialist Competitive Algorithm and Monte Carlo simulation. Finally, this paper presents a real application of the proposed model and the designed hybrid algorithm for predicting the efficiency of five gas stations for the next two periods of them, with using real information which gathered from credible sources. The results will be compared with the Qin’s hybrid algorithm in terms of solution quality and runtime.
N. Shirazi; M. Seyyed Esfahani; H. Soleimani
Volume 2, Issue 1 , June 2015, , Pages 27-40
Abstract
This paper considers a three-stage fixed charge transportation problem regarding stochastic demand and price. The objective of the problem is to maximize the profit for supplying demands. Three kinds of costs are presented here: variable costs that are related to amount of transportation cost ...
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This paper considers a three-stage fixed charge transportation problem regarding stochastic demand and price. The objective of the problem is to maximize the profit for supplying demands. Three kinds of costs are presented here: variable costs that are related to amount of transportation cost between a source and a destination. Fixed charge exists whenever there is a transfer from a source to a destination, and finally, shortage cost that incurs when the manufacturer does not have enough products for supplying customer’s demand. The model is formulated as a mixed integer programming problem and is solved using a multicriteria scenario based solution approach to find the optimal solution. Mean, standard deviation, and coefficient of variation are compared as the acceptable criteria to decide about the best solution.
M. Ramezani
Volume 1, Issue 1 , November 2014, , Pages 31-42
Abstract
Supply chain network design (SCND) problem has recently been gaining attention because an integrated management of the supply chain (SC) can reduce the unexpected/undesirable events and can affect definitely the efficiency of all the chain. A critical component of the planning activities of a manufacturing ...
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Supply chain network design (SCND) problem has recently been gaining attention because an integrated management of the supply chain (SC) can reduce the unexpected/undesirable events and can affect definitely the efficiency of all the chain. A critical component of the planning activities of a manufacturing firm is the efficient design of its SC. Hence, SCND affords a sensitive platform for efficient and effective supply chain management and is an important and strategic decision in one. This paper presents a supply chain network model considering both strategic and tactical decisions. The model determines location of plants and distribution centers regarding single sourcing and capacity of plants and distribution centers (strategic level) while the shipments have to wait in the queue for transporting from plants to distribution centers (tactical level), which lead to the lead time is incorporated in model. Because of high-impact decision of a supply chain network design, we extend the model in an uncertain environment. To deal with uncertainty where the uncertain parameters are described by a finite set of possible scenarios, the two-stage stochastic programming approach is applied. Finally, a numerical example is given to demonstrate the significance of problem.
A. Ardavan; A. Alem Tabriz
Volume 3, Issue 2 , December 2016, , Pages 33-57
Abstract
Supply chain design has a crucial role in the prosperity and sustainable growth of enterprises. Network and innovation mutual relationship shapes the orientation and design of the supply chain. Networks are means of securing access to the resources, information and support. A number of studies have examined ...
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Supply chain design has a crucial role in the prosperity and sustainable growth of enterprises. Network and innovation mutual relationship shapes the orientation and design of the supply chain. Networks are means of securing access to the resources, information and support. A number of studies have examined the relationship between networks and innovation, and show a positive relation between them which results in growth. The contingent nature of networking in the literature makes it a complex phenomenon for an entrepreneur to identify his/her optimal position in the web of networks and master it effectively to provide sustainable presence in the market. This paper examines different types of networking in a broad term and innovation in the context of enterprises and shows the interdependency of networking and innovation. An in-depth review of the extant literature and the grounded theory is applied to develop a conceptual framework for elements of the supply chain by exploring the major layers of networks, innovation and their mutual relationship. Based on this model, several studies are reviewed and this paper offers suggestions in order to understand how the network and innovation reciprocal relationship influences performance.
Esmaeil Akhondi Bajegani; Seyed hosein Eiranmanesh; Amirreza Zare
Abstract
Nowadays, not only improving service levels is not sufficient for consumer satisfaction, but also, the consumers themselves determine product or service quality. In other words, we can interpret quality as "the degree of accordance with the consumer's need." Therefore, we should look for solutions to ...
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Nowadays, not only improving service levels is not sufficient for consumer satisfaction, but also, the consumers themselves determine product or service quality. In other words, we can interpret quality as "the degree of accordance with the consumer's need." Therefore, we should look for solutions to identify consumers' needs and requirements for applying them in the design and development of the product or service. One of these methods is the Kano model. This model shows the decision maker if any of the consumers' requirements are in the product/service or not and how much it will affect their satisfaction. This tool classifies consumers' needs for converting them to design requirements. But, human mentality and behavior always are accompanied by uncertainties. Linguistic variables or fuzzy numbers have been used in the literature to overcome this defect. Researchers developed the fuzzy Kano's model using this method and enhanced the model's efficiency compared to the deterministic one. The efficiency of this model has increased compared with the deterministic one. However, the decision-makers are unsure how to classify customers' needs using this strategy. This research uses a Fuzzy Inference System (FIS) to tackle this challenge. The essential contribution is developing a fuzzy Kano's model based on FIS for consumer requirements analysis. A case study from the restaurant industry in Yazd city of Iran was considered to validate the proposed model. The results show the superior performance of the proposed model compared with fuzzy Kano's model in recognizing consumers' needs.
Sajed Rastbin; Farhang Mozaffar; Mostafa Behzadfar; Mehrdad Gholami Shahbandi
Abstract
Motorized transportation systems in the urban areas witnessed huge developments in the infrastructures thanks to the advances in various aspects of technology. This urbanization revolution has its own pros and cons. The resulting dominance of vehicles has limited the presence of people in public places ...
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Motorized transportation systems in the urban areas witnessed huge developments in the infrastructures thanks to the advances in various aspects of technology. This urbanization revolution has its own pros and cons. The resulting dominance of vehicles has limited the presence of people in public places and their participation in social activities, threatening the human based lifestyle of the cities. Historic districts are of most affected areas which withstand the unwanted consequences of such an experience. These areas play a substantial role in urban activities by providing great social activity and walking zones for pedestrians. Hence, in recent years, urban management has paid attention to this endanger regions in order to sustain and enhance their properties by introducing some pedestrianization plan as urban regeneration policies. To design an effective plan, it is necessary to figure out how people behave in response to their environment. Pedestrian modeling is the key to the problem and is studied in the past few decades, mostly in microscopic scale. In addition, a logical decision-making process is required to choose the option with the best outcome in this complex system, considering financial limits of strategic urban planning. In this paper, a macroscopic multi-class user equilibrium pedestrian assignment algorithm is proposed to anticipate the route choice behavior of the pedestrians in a network, and a decision making platform for the pedestrian network design is presented using bi-level mathematical mixed-integer programming and genetic algorithm. The presented model determines the best possible projects to be implemented on the network, considering the constraints of the historic districts. The model brings forward an intelligent framework to help the urban planners in spending the minimum cost, while maximizing some predefined objectives. The proposed method is applied to solve the problem in a test network and in a real case scenario for the historic district of the city of Tehran. The results prove the validity and the efficiency of the algorithm.
Ehsan Mardan; Rezvane Kashani; Reza Kamranrad
Volume 10, Issue 1 , July 2023, , Pages 34-52
Abstract
Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. ...
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Supply chains in the world are increasingly exposed to disruptions caused by disasters in every part of the world. The emergence of risk in today's business environment due to globalization, disruptions, poor infrastructure, forecast errors and various uncertainties affects every management decision. The present study was an attempt to propose an emergency order and production planning for a multi-product multi-item problem where products are made up of several ingredients. A side from the main supplier, the backup supplier can be used to supply each component where orders must be delivered within a certain time interval (specified time window). In the present study attempts are made to use sourcing strategies to realize supply chain flexibility under disruptions. A scenario-based mathematical model encompassing different uncertainties such as those arising from disruption and operational risks is formulated. A case study analysis is carried out to appraise the output of risk attitudes adopted by different decision-makers (both risk-neutral and risk-averse). The present study presents strategies to create flexible supply bases that diminish the cost of the worst scenario in the face of supply chain risks. By increasing the number of primary and supporting suppliers, VAR and C-VR values will increase, so the management offer is that the number of suppliers should be kept constant within acceptable limits to prevent a sharp increase in the number of suppliers. Suppliers should release orders in time by establishing time windows and setting deadlines in order to receive orders. Also, this paper shows that the values of VAR and C-VR decrease with the increase of primary supply capacity, and with the increase of primary supply capacity, costs are reduced by about 99%, which reduces the effect of disruption on the capacity of primary suppliers.
Mohammad Ehsanifar; Nima Hamta; Mahshid Hemesy
Abstract
This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing ...
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This paper includes a simulation model built in order to predict the performance indicessuch aswaiting time by analyzing queue’s components in the real world under uncertain and subjective situation. The objective of this paper is to predict the waiting time of each customer in an M/M/C queuing model. In this regard, to enable decision makers to obtain useful results with enough knowledge on the behavior of system, the queuing system is considered in fuzzy environment in which the arrival and service times are represented by fuzzy variables. The proposed approach for vague systems can represent the system more accurately, and more information is provided for designing queueing systems in real life. Furthermore, simulation method is applied successfully for modeling complex systems and understanding queuing behavior. Finally, a numerical example as a case study in a banking system is solved to show the validity of developed model in the real situation.
Masoud Rabbani; Fatemeh Navazi; Niloofar Eskandari; Hamed Farrokhi-Asl
Abstract
Non-uniform distribution of customers in a region and variation of their maximum willingness to pay at distinct areas make regional pricing a practical method to maximize the profit of the distribution system. By subtracting the classic objective function, which minimizes operational costs from revenue ...
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Non-uniform distribution of customers in a region and variation of their maximum willingness to pay at distinct areas make regional pricing a practical method to maximize the profit of the distribution system. By subtracting the classic objective function, which minimizes operational costs from revenue function, profit maximization is aimed. A distribution network is designed by determining the number of trucks to each established distribution center, allocating customers in routes, and inventory levels of customers. Also, environmental impacts, including fuel consumption and CO2 emission, aimed to be minimized. So, a new quadratic mixed-integer programming model is presented for the Green Transportation Location-Inventory-Routing Problem integrated with dynamic regional pricing problem (GTLIRP+DRP). The model is applied to the real case study, to show its competent application. To tackle this problem, a Hybrid Bees Algorithm (HBA) is developed and verified by the genetic algorithm. Finally, managers suggested using HBA that achieves better solutions in the less computational time.
F. Gholian Jouybari; A. J. Afshari; M. M. Paydar
Volume 3, Issue 1 , June 2016, , Pages 39-60
Abstract
In this paper, we consider the fuzzy fixed-charge transportation problem (FFCTP). Both of fixed and transportation cost are fuzzy numbers. Contrary to previous works, Electromagnetism-like Algorithms (EM) is firstly proposed in this research area to solve the problem. Three types of EM; original EM, ...
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In this paper, we consider the fuzzy fixed-charge transportation problem (FFCTP). Both of fixed and transportation cost are fuzzy numbers. Contrary to previous works, Electromagnetism-like Algorithms (EM) is firstly proposed in this research area to solve the problem. Three types of EM; original EM, revised EM, and hybrid EM are firstly employed for the given problem. The latter is being firstly developed and proposed in this paper. Another contribution is to present a novel, simple and cost-efficient representation method, named string representation. It is employed for the problem and can be used in any extended transportation problems. It is also adaptable for both discrete and continues combinatorial optimization problems. The employed operators and parameters are calibrated, according to the full factorial and Taguchi experimental design. Besides, different problem sizes are considered at random to study the impacts of the rise in the problem size on the performance of the algorithms.
Elnaz Babazadeh; Jafar Pourmahmoud
Abstract
Super-efficiency model in the presence of negative data is a relatively neglected issue in the DEA field. The existing super-efficiency models have some shortcomings in practice. In this paper, a novel VRS radial super-efficiency DEA model based on Directional Distance Function (DDF) is proposed to provide ...
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Super-efficiency model in the presence of negative data is a relatively neglected issue in the DEA field. The existing super-efficiency models have some shortcomings in practice. In this paper, a novel VRS radial super-efficiency DEA model based on Directional Distance Function (DDF) is proposed to provide a complete ranking order of units (including efficient and inefficient ones). The proposed model is feasible no matter whether data are non-negative or not. This model shows more reliability on differentiating efficient units from inefficient ones via a new bounded super-efficiency measure. It can project each unit onto the super-efficiency frontier along a new non-negative direction and produce improved targets for inefficient units. The model overcomes the infeasibility issues occur in Nerlove–Luenberger supper-efficiency model. The proposed model conveys good properties such as monotonicity, unit invariance and translation invariance. Apart from numerical examples, an empirical study in bank sector demonstrates the superiority of the proposed model.
Seyed Mohammad Hassan Hosseini
Abstract
The two-stage assembly flowshop scheduling problem has been studied in this research. Suppose that a number of products of different kinds are needed to be produced. Each product is consists of several parts. There are m uniform machines in the first stage to manufacture the components (parts) of products ...
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The two-stage assembly flowshop scheduling problem has been studied in this research. Suppose that a number of products of different kinds are needed to be produced. Each product is consists of several parts. There are m uniform machines in the first stage to manufacture the components (parts) of products and there is one assembly station in the second stage to assembled parts into products. Setup operation should be done when a machine starts processing a new part and setup times are treated as separate from processing times. Two objective functions are considered: (1) minimizing the completion time of all products (makespan) as a classic objective, and (2) minimizing the cost of energy consumption as a new objective. Processing speed of each machine is adjustable and the rate of energy consumption of each machine is dependent of its processing speed. At first, this problem is described with an example, and then needed parameters and decision variables are defined. After that, this problem is modeled as a mixed integer linear programming (MILP) and GAMS software is applied to solve small problems. To solve this bi-objective model, Epsilon Constraint algorithm is used on some test problems obtained standard references. Data of test problems were obtained from previous references and new parameters have been adjusted for considered problem. Conflicting of two considered objective functions has been valid through the result. In additional, result of solving test problems and sensitivity analysis show that how we can reduce energy consumption by adjusting completion times.
Ali Salmasnia; Ali Tavakoli; Maryam Noroozi; Behnam Abdzadeh
Abstract
Control charts are powerful tools to monitor quality characteristics of services or production processes. However, in some processes, the performance of process or product cannot be controlled by monitoring a characteristic; instead, they require to be controlled by a function that usually refers as ...
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Control charts are powerful tools to monitor quality characteristics of services or production processes. However, in some processes, the performance of process or product cannot be controlled by monitoring a characteristic; instead, they require to be controlled by a function that usually refers as a profile. This study suggests employing exponentially weighted moving average (EWMA) and range (R) control charts for profile monitoring, simultaneously. For this purpose, the parameters of these control charts should be determined in a way that the expected total cost is minimized. In order to evaluate the statistical performance of the proposed model, the in-control and out-of-control average run lengths are applied. Moreover, the existence of uncertain parameters in many processes is a barrier to attain the best design of control charts in practice. In this paper, the economic-statistical design of control charts for linear profile monitoring under uncertain conditions is investigated. A genetic algorithm is used for solving the proposed robust model, and the Taguchi experimental design is employed for tuning its parameters. Furthermore, the effectiveness of the developed model is illustrated through a numerical example.
Mojtaba Arab Momeni; Saeed Yaghoubi; Mina Ebrahimi Arjestan
Abstract
Enterprise resources planning (ERP) systems attract many attentions from industry sector because of their ability to facilitate and integrate the enterprise operations. However, many expenses accompany the implementation of these systems and consecutive changes which doing a precise and comprehensive ...
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Enterprise resources planning (ERP) systems attract many attentions from industry sector because of their ability to facilitate and integrate the enterprise operations. However, many expenses accompany the implementation of these systems and consecutive changes which doing a precise and comprehensive performance evaluation a necessary part of this process. These evaluations should consider operational and technical aspects of ERP systems to reflect the effectiveness of them toward the organization's requirements. In this paper, a two-stage data envelopment analysis model (DEA) is presented in order to evaluate the efficiency of ERP systems in such a way that the operational and the technical aspect are evaluated in the first stage and the second stage of DEM model, respectively. Based on the obtained results the ERP systems’ functionality and customizability to the client processes are the two key features that need to be considered by the providers. Furthermore, the findings of parameter sensitivity analysis of the proposed model provide deep and managerial insights into the further usability improvements of ERP systems.
R. Hassanzadeh; I. Mahdavi; N. Mahdavi-Amiri
Volume 2, Issue 1 , June 2015, , Pages 41-60
Abstract
Here, a collection of base functions and sub-functions configure the nodes of a web-based (digital)network representing functionalities. Each arc in the network is to be assigned as the link between two nodes. The aim is to find an optimal tree of functionalities in the network adding value to the ...
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Here, a collection of base functions and sub-functions configure the nodes of a web-based (digital)network representing functionalities. Each arc in the network is to be assigned as the link between two nodes. The aim is to find an optimal tree of functionalities in the network adding value to the product in the web environment. First, a purification process is performed in the product network to assign the links among bases and sub-functions. Then, numerical values as benefits and costs are determined for arcs and nodes, respectively. To handle the bi-objective Steiner tree, a particle swarm optimization algorithm is adapted to find the optimal tree determining the value adding sub-functions to bases in a convergent product. An example is worked out to illustrate the applicability of the proposed approach.
F. Bagheri; M.J. Tarokh
Volume 1, Issue 1 , November 2014, , Pages 43-57
Abstract
Companies’ managers are very enthusiastic to extract the hidden and valuable knowledge from their organization data. Data mining is a new and well-known technique, which can be implemented on customers data and discover the hidden knowledge and information from customers' behaviors. Organizations ...
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Companies’ managers are very enthusiastic to extract the hidden and valuable knowledge from their organization data. Data mining is a new and well-known technique, which can be implemented on customers data and discover the hidden knowledge and information from customers' behaviors. Organizations use data mining to improve their customer relationship management processes. In this paper R, F, and M variables for each customer are defined and extracted. Customers are clustered by using K-mean algorithm based on their calculated R, F and M values. The best number of clusters is calculated by Davies Bouldin index. The clusters are ranked based on their eligibility values. By analyzing the clustering results, we propose some offers to the company to calculate the premiums and insurance charges.
H. Golpira; M. Zandieh; E. Najafi; S. Sadi Nezhade
Volume 2, Issue 2 , December 2015, , Pages 43-54
Abstract
Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model ...
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Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model considers minimization of supply chain costs while the second objective function minimizes CO2 emission level. The Conditional Value at Risk (CVaR) approach is used to deal with the demand uncertainty in supply chain network in addition to the scenario based approach that is employed to deal with the stochastic level of CO2 emission. The implementation of the proposed model has been demonstrated using some randomly selected numbers and the results are analyzed accordingly.
Maryam Noroozi; Mohammad Reza Gholamian
Abstract
In the proposed study, an inventory model of a two-echelon green perishable supply chain which consists of one manufacturer and one retailer is investigated. The produced items have a deterministic shelf life and will be removed from the shelves when they reach to their expiration date. A novel formulation ...
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In the proposed study, an inventory model of a two-echelon green perishable supply chain which consists of one manufacturer and one retailer is investigated. The produced items have a deterministic shelf life and will be removed from the shelves when they reach to their expiration date. A novel formulation of the demand function is also presented, which is a multiplicative function of time after replenishment, retail price, and green improvement level. The formulated demand function increases with the time to expiration and the green improvement degree; it also decreases with the retail price. The mentioned characteristics in this supply chain are derived from the industries of selling fruits, vegetables, meat and poultry, as well as dairy products. The manufacturer is considered the leader of the Stackelberg game, and three approaches are proposed to solve the inventory model: Decentralized, Centralized, and Coordinated by the revenue and green technology investment cost sharing contract, which guarantees more profit for each member than the decentralized decision-making approach. The numerical results demonstrate that the proposed revenue-sharing contract could successfully help the supply chain members to achieve the potential supply chain profit in the centralized approach. A comparative study is also conducted to show the differences between implementing and not implementing green technology investments, which shows the profitability of making green technology investments when consumers have green preferences. It was observed that as the reservation cost increases, the importance of investments in green technology will increase for both parties. Also, with high potential market demand, it is more beneficial to invest in green technology. This study deals with a contribution to the formulation of the demand function, as a novel multiplicative function of time after replenishment in the form of power function, and retail price and green improvement level in the form of complementary linear function.
Mansoureh Maadi; Mohammad Javidnia
Abstract
Precedence constrained sequencing problem (PCSP) is related to locate the optimal sequence with the shortest traveling time among all feasible sequences. In PCSP, precedence relations determine sequence of traveling between any two nodes. Various methods and algorithms for effectively solving the PCSP ...
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Precedence constrained sequencing problem (PCSP) is related to locate the optimal sequence with the shortest traveling time among all feasible sequences. In PCSP, precedence relations determine sequence of traveling between any two nodes. Various methods and algorithms for effectively solving the PCSP have been suggested. In this paper we propose a cuckoo search algorithm (CSA) for effectively solving PCSP. CSA is inspired by the life of a bird named cuckoo. As basic CSA at first was introduced to solve continuous optimization problem, in this paper to find the optimal sequence of the PCSP, some schemes are proposed with modifications in operators of the basic CSA to solve discrete precedence constrained sequencing problem. To evaluate the performance of proposed algorithm, several instances with different sizes from the literature are tested in this paper. Computational results show the good performance of the proposed algorithm in comparison with the best results of the literature.
Hamid Reza Aghamiri; Esmaeil Mehdizadeh; Habib Reza Gholami
Volume 10, Issue 1 , July 2023, , Pages 53-66
Abstract
Today, the proper and effective performance of employees is one of the keys to the success of organizations. Good performance refers to high efficiency, quality, profitability, and customer orientation. One of the most important duties of human resource managers is to design and establish employee performance ...
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Today, the proper and effective performance of employees is one of the keys to the success of organizations. Good performance refers to high efficiency, quality, profitability, and customer orientation. One of the most important duties of human resource managers is to design and establish employee performance evaluation systems. Since qualitative indices have a major share of these indices, judgmental methods are generally used for ranking them. Decision makers assign weights to these indices based on their attitudes and rank the employees. Hence, these methods fail to fully explain the performance of organizations’ employees and are influenced by some degrees and levels of ambiguity. Fuzzy logic methods are highly useful for resolving the ambiguities in these alternatives. In this paper, we propose an employee performance evaluation method with a type-2 fuzzy ranking approach. In our proposed method, a job ID is designed based on optimal models while an employee ranking method is developed and explained using the trapezoidal interval type-2 fuzzy ranking model introduced by Chen et al. 2012. In the end, the proposed method is utilized for the performance evaluation of employees in a real company.
Sara Tavassoli; Farnaz Shahpar; Taha-Hossein Hejazi
Abstract
Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability ...
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Most of the existing approaches for fuzzy reliability analysis are based on fuzzy probability. The aim of this paper is to describe fuzzy reliability using fuzzy differential equation. The reliability of a system in real world applications is affected by some uncertain parameters. Fuzzy reliability is a way to present the reliability function uncertainly using fuzzy parameters. In the proposed fuzzy differential equation for reliability, two types of fuzzy derivative: Hukuhara derivative and generalized differentiability are used. It is proved that the Hukuhara differentiability is not adequate for fuzzy reliability analysis. Finally, using the fuzzy integration, the concept of fuzzy mean time to failure (FMTTF) will be introduced. Some numerical simulations are presented to show the applicability and validity of generalized differentiability, in comparison with the Hukuhara differentiability results for fuzzy reliability analysis.