Milad Hematian; Mirmehdi Seyyedesfahani; Iraj Mahdavi; Nezam Mahdavi Amiri; Javad Rezaeian
Abstract
One of the most important aspects of human resource management is the allocation of the workforce to activities. Human resource assignment to project activities for its scheduling is one of the most real and common issues in project management and scheduling. This becomes even more significant when human ...
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One of the most important aspects of human resource management is the allocation of the workforce to activities. Human resource assignment to project activities for its scheduling is one of the most real and common issues in project management and scheduling. This becomes even more significant when human resource assignment to multiple projects simultaneously is considered. On the one hand, workforces can have multi skills due to technological and scientific development so that they can be assigned to project activities based on their skill level. On the other hand, the learning effect is also taken into account to make the model more realistic. These factors can affect completion time, total cost and execution quality of projects. In this study, a multi-objective optimization model for multi-project scheduling and multi-skilled human resource assignment problem based on the learning effect and activities' quality is presented. A mixed-integer linear programming model (MILP) is developed for the proposed problem and solved by the ε-constraint method in GAMS software. Managers can select a solution based on their priority. Finally, a sensitivity analysis is done on the learning and forgetting effect to investigate their impacts on each objective function.
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.
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.
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.
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.
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.