Yazar "Nosrati, Mahmood" seçeneğine göre listele

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    Bi objective hybrid vehicle routing problem with alternative paths and reliability
    (GROWING SCIENCE, 611, 141 DAVISVILLE AVE, TORONTO, ON M4S 1G7, CANADA, 2020) Nosrati, Mahmood; Khamseh, Alireza Arshadi
    The hybrid vehicle routing problem is an extension of the green vehicle routing problem where vehicles can use different fuels. In this research, a bi-objective hybrid vehicle routing problem is presented and solved by considering alternative paths, various lengths and reliabilities. The first objective function minimizes overall system costs, fuel consumption, and greenhouse gas emissions, whereas the second objective function maximizes the reliability of the entire system with alternative paths and several reliabilities. The proposed model is formulated as mixedinteger nonlinear programming and a bi-objective simulated annealing (MOSA) algorithm along with the e-constraint method is used as solution strategy. The implementation of the proposed method is presented using some numerical instances.
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    Distance discount in the green vehicle routing problem offered by external carriers
    (SPRINGER INT PUBL AG, GEWERBESTRASSE 11, CHAM CH-6330, SWITZERLAND, 2020) Nosrati, Mahmood; Khamseh, Alireza Arshadi
    This study suggested a model for the Green Vehicle Routing Problem (GVRP) regarding distance discount strategy. For the frst time,we defned distance discount strategy based on intervals for a vehicle routing problem. The proposed model attempts to minimize the total cost of the system by selecting the diferent vehicles and paths that have time and fuel constraints while external carriers ofer the distance discount. This model is formulated by mixed-integer linear programming and classifed as NP-hard. The feasibility of this issue depends on the location of customers and fuel stations. Two metaheuristic algorithms such as tabu search (TS) and simulated annealing (SA) have been developed beside the exact method, and the efciency of our metaheuristic methods have been examined through 40 benchmark instances of different sizes and 16 randomly generated numerical instances. Computational results show superior performance of the simulated annealing in comparison with the tabu search for test problems and the cost efciency owing to the distance discount from the organization’s outlook.
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    Öğe
    Reliability optimization in a four-echelon green closed-loop supply chain network considering stochastic demand and carbon price
    (Growing Science, 2020) Nosrati, Mahmood; Khamseh, Alireza Arshadi
    In recent years, one of the goals of any company is to increase overall production and process reliability. Hereupon supply chain reliability has been gaining growing attention and provides a technical framework for quantifying supply chain risks and uncertainties. In this paper, supply chain reliability was investigated in a two-stage stochastic programming model to design reliable closed-loop green four-echelon forward/backward supply chain networks. The purpose of this model was to maximize the total reliability of the supply chain based on the structural reliability theory. Our proposed model also minimized the cost of the supply chain by definition of recycling centres and the cost of penalizing unauthorized carbon emission and damages. The model optimized the locations of factories, warehouses, and recycling centres considering stochastic modes for demands and carbon price, as well as the flow between different sectors and the optimal orders. As the proposed model was a mixed-integer nonlinear problem, both e-constraint method and the metaheuristic algorithm (NSGA-II) were used in different scales and the sensitivity analysis was performed for critical parameters. © 2020 by the authors; license Growing Science, Canada.