Morteza Shafiee; Sara Emadi
Abstract
Today, outsourcing is recognized as one of the most effective strategies in the business world. In this regard, outsourcing of business processes is considered to be one of the most common forms of outsourcing. The purpose of this study is to provide In-depth and quantitative analysis of the benefits ...
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Today, outsourcing is recognized as one of the most effective strategies in the business world. In this regard, outsourcing of business processes is considered to be one of the most common forms of outsourcing. The purpose of this study is to provide In-depth and quantitative analysis of the benefits of BPO in a dairy plant in Iran and how these benefits affect the willingness of senior plant managers to increase the levels of outsourcing of business processes. Therefore, Structural Equation Modeling (SEM) based on BPO Benefit Analysis is used. The population of the study consisted of 50 managers who all answered a questionnaire containing 20 questions. Responses were analyzed using the Partial Least Squares (PLS) method. The research method is a quantitative experimental one. The findings of this study show that cost planning has a higher value than real cost savings and this is one of the benefits of BPO.
Behzad Maleki Vishkaei; Iraj Mahdavi; Nezam Mahdavi Amiri; Esmaile Khorram
Abstract
Public Bicycle Sharing System (PBSS) is used as a way to reduce traffic and pollution in cities. Its performance is related to availability of bicycles for picking up and free docks to return them. Existence of different demand types leads to the emergence of imbalanced stations. Here, we try to balance ...
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Public Bicycle Sharing System (PBSS) is used as a way to reduce traffic and pollution in cities. Its performance is related to availability of bicycles for picking up and free docks to return them. Existence of different demand types leads to the emergence of imbalanced stations. Here, we try to balance inventory of stations via defining maximal response rates for each type of rental request. If the maximal response rate for a destination is lower than 100 percent, a part of the proposed destination requests is rejected in the hope of balancing the inventory. The goal is to minimize the mean extra inventory and the mean rejected requests by providing proper amounts of the maximal response rates. An approximation method named as Mean Value Analysis (MVA) is used to develop a genetic algorithm for solving the problem. Different examples are worked through to examine the applicability of the proposed method. The results show that the proposed policy leads to a significant improvement and reduces the users’ dissatisfaction.
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.
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.
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.
Hamed Homaei; Iraj Mahdavi; Ali Tajdin
Abstract
One of the main concerns of all industries such as mine industries is to increase their profit and keep their customers through improving quality level of their products; but increasing the quality of products usually releases air pollutants. Nowadays the management of air pollutant emissions with harmful ...
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One of the main concerns of all industries such as mine industries is to increase their profit and keep their customers through improving quality level of their products; but increasing the quality of products usually releases air pollutants. Nowadays the management of air pollutant emissions with harmful environmental and health effects is one of the most pressing problems. In this paper, authors study the decision behaviour and coordination issue of a mining metal three-level supply chain with one supplier (extractor), one mineral processor and one manufacturer. We compare the decentralized and the centralized systems and reduce air pollutant emission by designing a revenue sharing contract for the mentioned decentralized supply chain under cap-and-trade regulation. Finally, a numerical example shows that the designed contract not only provides win-win condition for all supply chain members and increases whole supply chain profit but also reduces harmful air pollutant emissions in the supply chain.
Ahmad Ali Abedinpour; Mohsen Yahyaei; Armin Jabbarzadeh
Abstract
Addressing an integrated decision-making structure for planting and harvesting scheduling may lead to more realistic, accurate, and efficient decision in fresh product supply chain. This study aims to develop an integrated bi-objective tactical and operational planning model for producing and distributing ...
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Addressing an integrated decision-making structure for planting and harvesting scheduling may lead to more realistic, accurate, and efficient decision in fresh product supply chain. This study aims to develop an integrated bi-objective tactical and operational planning model for producing and distributing fresh crops. The first objective of the model is to maximize total revenue of supply chain. Over the past few years, there has been a considerable shift in emphasis in social responsibility of supply chains. Therefore, a key purpose of this article is to plan a socially responsible fresh agricultural supply chain as the second objective function. The proposed bi-objective model seeks to make optimal decisions on planting, harvesting scheduling (harvesting pattern), selecting the transport fleet type, and products supply channel to the consumers. To conduct the analysis, numerical examples are provided based on a real case study and the true Pareto front is achieved with augmented ε-constraint method. The results indicated the applicability of the proposed model and verified its validity. Moreover, comparison between total weighting and ε-constraint method is provided to ensure the efficiency of Pareto solutions.
Faezeh Motevalli-Taher; Mohammad Mahdi Paydar
Abstract
In this study, tactical decisions considering the material and financial flows in a supply chain have been made. To achieve these aims and some effective solutions, a multi-objective mathematical model proposed for an integrated supply chain master planning problem. The multi-product, multi-period and ...
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In this study, tactical decisions considering the material and financial flows in a supply chain have been made. To achieve these aims and some effective solutions, a multi-objective mathematical model proposed for an integrated supply chain master planning problem. The multi-product, multi-period and capacitated supply chain network has three objective functions. Two first objective functions are maximizing the net present value of manufacturing centers and suppliers’ cash flow, and the third one minimizes the market price of the final product. Besides we considered the market price as a key variable in the model and investigate its effects. Then, improved multi-choice goal programming is used to transform the multi-objective model to its single-objective one. To find out the appropriateness of the proposed model, the results of an industrial example are illustrated, and sensitivity analyses to evaluate the results are provided to obtain better insight and access to different aspects of the problem.
Peiman Ghasemi; Abdollah babaeinesami
Abstract
Considering the increasing growth of cities, population and urban fabric density, it seems necessary that emergency facilities and services such as fire stations are positioned optimally so that they can fulfill the demands well. The aim of this study is the optimization of equipment use in the fire ...
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Considering the increasing growth of cities, population and urban fabric density, it seems necessary that emergency facilities and services such as fire stations are positioned optimally so that they can fulfill the demands well. The aim of this study is the optimization of equipment use in the fire stations, minimization the time to arrive at the incident through management of referral call to 125 Sari fire station center so that the referral call to the nearest fire station do not remain unanswered as much as possible and there will be no need to refer to another station. In this research, the resources required at Sari’s fire station were simulated using Enterprise Dynamic software. The input data of the simulation is based on the number and sequence of the time of people's phone calls. After collecting historical data from telephone calls using the function fitting method, the distribution function of available resources is calculated in Minitab software. In the following, the distribution functions of failure in the existing fire engines are calculated using the same method and the obtained information is simulated. The result indicates an improvement of 20% in relief time by adding one source in Sari fire station center.
Nazila Adabavazeh; Mehrdad Nikbakht
Abstract
Airline industry is one of the main infrastructures for sustainable development of a country. The quality of the reverse support service will be effective in increasing the safety and health of the structures, reducing the impact of disasters and reducing costs. The aim of this study is to evaluate the ...
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Airline industry is one of the main infrastructures for sustainable development of a country. The quality of the reverse support service will be effective in increasing the safety and health of the structures, reducing the impact of disasters and reducing costs. The aim of this study is to evaluate the performance of an organization based on the main factors of reverse supply chain with the service quality approach using the Data Envelopment Analysis (DEA) model. In this research, firstly, performance indicators have been identified and then the efficiency of the 24 main factors of reverse supply chain success in the airline industry is determined by the output-oriented DEA-BCC model. The main efficient and inefficient factors are determined by EMS software. Performance measurement can be very useful for managers to allocate resources because it can provide patterns for inefficient units to achieve efficiency and performance improvements.
Iraj Mahdavi; Sara Firouzian; Mohammad Mahdi Paydar; Mahdi Saadat
Abstract
Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in ...
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Cell formation problem (CFP) is one of the main problems in cellular manufacturing systems. Minimizing exceptional elements and voids is one of the common objectives in the CFP. The purpose of the present study is to propose a new model for cellular manufacturing systems to group parts and machines in dedicated cells using a part-machine incidence matrix to minimize the voids. After identifying the exceptional elements, the machines required for processing the remained operations of corresponding parts which are not processed in the dedicated cells are specified. This results in a new matrix called part family-machine. Then, by clustering the part family-machine incidence matrix, the part families that should be assigned to a specific cell to achieve the highest similarity can be determined. The similarity can be translated to sharing machines required for completing the processes and form new cells called shared cells to minimize the number of exceptional elements and voids. Unlike previous models in which the similarity is considered only in the dedicated cells, in the proposed model, the similarity would be monitored and observed in the entire production process. Due to the complexity of our model, two meta-heuristic algorithms including artificial immune system (AIS) and simulated annealing (SA) are proposed. The efficiency of the algorithms is compared to that of exact solutions. Also, the algorithms are compared regarding the quality of solutions. Finally, according to grouping efficacy measure, SA algorithm has a superior performance in comparison with AIS by spending less CPU 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.