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- 저자 : R. Tavakkoli-Moghaddam (검색결과 2 건)
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Robust Periodic Vehicle Routing Problem with Time Windows under Uncertainty: An Efficient Algorithm
A. Salamatbakhsh-Varjovi,R. Tavakkoli-Moghaddam,M. Alinaghian,E. Najafi 대한토목학회 2018 KSCE JOURNAL OF CIVIL ENGINEERING Vol.22 No.11
In a competitive environment, distributors engage in intense rivalry to meet the customers’ demands and accordingly earn maximum profits. Due to changes in customers’ demands, changes in a planned combination of customers to be visited in various days, traffic changes, etc., a sequence of visiting customers by competitors will be changed. So, planning for serving customers ahead of competitors will be uncertain. On the other hand, total transportation costs are also of high importance in distribution of goods. By keeping this issue in mind, we develop a bi-objective mathematical model to evaluate a Periodic Vehicle Routing Problem (PVRP) with time windows under uncertainty for companies competing to provide services to customers. The model is established using an improved scenario-based robust optimization approach. Given that the PVRP is an NP-hard problem, an Improved Differential Evolution (IDE) algorithm is used to identify efficient solutions for the model. The results on small-scale problems were compared with those obtained using the CPLEX solver. To evaluate the performance of the proposed IDE algorithm, a few sample tests on large-scale problems are conducted, and the results are compared with those derived using two other differential evolution algorithms. The findings show that the IDE algorithm exhibits suitable accuracy and performance in solving the presented model.
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S. M. Hatefi,F. Jolai,S. A. Torabi,R. Tavakkoli-Moghaddam 대한토목학회 2015 KSCE JOURNAL OF CIVIL ENGINEERING Vol.19 No.4
Although disruptions rarely occur in the logistics networks, they can cause serious operational consequences and negative financial effects in the long-term. This paper proposes a fuzzy possibilistic programing model for designing a reliable forward-reverse logistics network with hybrid facilities in the presence of both uncertainty and random facility disruptions. For doing so, first several effective reliability strategies, i.e., introducing two kinds of reliable and unreliable facilities, partial and complete capacity disruptions, and a sharing strategy, are defined and incorporated into the developed reliability model to mitigate the impacts of random facility disruptions and improve resiliency of the network. Furthermore, a fuzzy possibilistic programing is utilized to deal with the existing epistemic uncertainties in the network parameters, i.e., fixed opening costs, variable processing and transportation costs, demands, returned products, and capacities. Finally, several numerical tests and also a sensitivity analysis are done to demonstrate the effectiveness and applicability of the proposed model in addition to the potency of the fuzzy possibilistic based solution method in this context.
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