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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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    A Bi objective uncapacitated multiple allocation p-hub median problem in public administration considering economies of scales
    (ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2021) Tofighian, Aliasghar; Khamseh, Alireza Arshadi
    This paper addresses uncapacitated multiple allocation p-hub median problems, which deals with both the constructors’ and the users’ objectives in order to obtain an economically sustainable system. One objective is maximizing the overall investment return in road and hub construction and the users’ satisfaction is translated by minimization of the overall usage cost. The problem is formulated in a way that can cover three possible policies as: Governmental requirement, constructor’s break-even point and predefined make span. To make these models more pragmatic, variable discount factors are used in preference to fixed ones. Accordingly, a comprehensive discussion about discount factors and their components has been included to justify the use of variable discount factors. Then some meta-heuristic algorithms like the Imperialist competitive algorithm (ICA), and an enhanced variation of a well-known multi-objective genetic algorithm called nondominated sorting genetic algorithm II (NSGA-II) are developed and applied to solve the problem. The performance of algorithms is compared to each other by utilizing some indicators such as hypervolume, ?-indicator, spacing metric, and CPU time. Computational experiments emphasize the need for using stated assumptions and the variable discount factor. It also confirms the efficiency of the proposed ICA.
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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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    Four Echelons Humanitarian Network Design Considering Capacitated/lateral Transshipment with a Destruction Radius and ABO Compatibility: Tehran Earthquake
    (Kharazmi University, 2023) Lohrasbpour, Majid; Khamseh, Alireza Arshadi; Nemati-Lafmejani, Reza; Naderi, Bahman
    During natural disasters, emergency sections try to find the best way to serve defective points and gradually find the optimal location of these service points as blood collection centers in safe areas to restore the system to its previous state. This research proposed a multi-objective mathematical model for the design of a four echelon comprehensive Blood Supply Chain (BSC) network in earthquakes. Here, the impact of the Earthquake Destruction Radius (EDR) on the BSC network and blood group compatibility have been considered simultaneously.In order to be more realistic the effect of multimodal capacitated transportation vehicles accompanied with lateral transshipment have been investigated. In our proposed model four multi-objective decision-making (MODM) methods, as well as the augmented ?-constraint method is adopted for finding Pareto optimal solutions. Finally, the validation of the problem has been explored by Bounded Objective Method (BOM). This model has been implemented based on the real data of Tehran; the capital of Iran; as one of the volunteer cities for tremendous earthquake in the world. © 2023 Authors. All rights reserved.
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    A multi-objective and multi-period model to design a strategic development program for biodiesel fuels
    (ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, 2019) Hosseinalizadeh, Ramin; Khamseh, Alireza Arshadi; Akhlaghi, Mohammad Mahdi
    The air pollution of conventional fuels, increases the tendency to alternative cleaner fuels like biodiesel fuels. Biodiesel is an expensive fuel and can be used as an additive to reduce levels of particulates, carbon monoxide, and other pollutants released from diesel fuel. The proportion of biodiesel in the produced fuel can be planned and controlled according to the conditions. This study forms a comprehensive multi-objective-period model for designing a biodiesel development program and compares different biodiesel blends and primary resources. The study considers B5, B10, B20, B40, and B100 along with diesel as the candidate fuels for demand fulfillment; furthermore, model considers waste cooking oil, soya, sunflower, and rapeseed as the primary resources. The objectives are the facilities' implementation costs and environmental effects minimization. The decision variables are the capacity planning and the facility location variables. The exact Pareto set is obtained by using the augmented e-constraint method. The study considers economic and environment objectives interactions. Based on the results, B5 and B40 are the most appropriate options in the exact Pareto set; moreover, the results show the advantages of this approach to select the most appropriate fuels and primary resources according to different conditions during the studied period.
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    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.