In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been...
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In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been investigated using evidence theory to mathematicalmodeling and solving by multi-objective optimization algorithms. In this regard, a multi-objectivemathematical model has been proposed, in which the first objective function aims to maximize a weighted selection of projects based on economic, environmental, technical, social, organizational, and competitive factors;the second objective function is focused on maximizing profit, and the third objective function is aimed at minimizing the risk of supply management. Moreover, various components, such as interest rates, carbon penalties, and other implementation limitations and additional constraints, have also been considered in the modeling and mathematical relationships to improve the model's performance and make it more relevant to real-world conditions and related issues, leading to better practical applications. In the mathematicalmodeling adopted, the processing time of project activities has been considered uncertain, and the evidence theory has been utilized. This method can provide a flexible and rational approach based on evidence and knowledge in the face of uncertainty. In addition, to solve the proposed multi-objectivemathematical model, metaheuristic optimization algorithms, such as the differential evolution (DE) algorithm based on the Pareto archive, have been used, and for evaluating the results, the non-dominated sorting genetic algorithm II (NSGA-II) has also been employed. Furthermore, the results have been compared based on multi-objective evaluation criteria, such as quality metric (QM), spacing metric (SM), and diversity metric (DM). It is worth noting that to investigate the performance and application of the proposed model, multiple evaluations have been conducted on sample prob
In this study, a typical supply chain network design problem consisting of plants, distribution centers, and customers is considered with the assumptions of multi-mode demand and multi-mode transportation. In it, the ...
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In this study, a typical supply chain network design problem consisting of plants, distribution centers, and customers is considered with the assumptions of multi-mode demand and multi-mode transportation. In it, the parameters of the problem are considered as a trapezoidal intuitionistic fuzzy value to handle the vagueness in the information. Based on it, a hybrid approach is proposed where the fuzzy objective function is converted to a set of crisp objective functions and the fuzzy constraints are crisped using their credibility measure. Finally, the crisp multi-objective formulation is obtained and solved it with different approaches. To evaluate the formulations and solution approaches, a case study from healthcare sector and several test problems are used. The results of computational experiments are used to compare the solution approaches, where the behavior of the proposed crisp formulation is fully discovered. (C) 2020 ISA. Published by Elsevier Ltd. All rights reserved.
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