Multiple Cross-docks Scheduling with Multiple Doors using Fuzzy Approach and Metaheuristic Algorithms

Movassaghi, Mitra; Darestani, Soroush Avakh

doi:10.1007/s40305-021-00362-9

Cited by 1 publication

(1 citation statement)

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“…On the other hand, Glover pointed out the ability of the TS algorithm for network design issues. In addition, the use of the fuzzy approach and meta-heuristic algorithms for complex problems is expanding (e.g., [15,16]). According to the studies done so far, this is the first time that GWO and TS algorithms are used for F2E-EVRP-MF-TW.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Two-Echelon Model to Optimize Energy Consumption in an Urban Logistics Network with Electric Vehicles

et al. 2022

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With the increase in pollutants, the need to use electric vehicles (EVs) in various urban logistics activities is an increasingly important issue. Currently, there are issues with the efficiency of transport companies in recognizing the effects of uncertain factors in daily logistics operations. Thus, this research proposes a novel fuzzy two-echelon vehicle routing problem involving heterogeneous fleet EVs and internal combustion vehicles (ICVs). The first echelon is recyclable wastes collected from waste pickup points and transported to the primary centers by EVs. The second echelon is transporting recyclable wastes to recycling centers by ICVs. In the proposed models, fuzzy numbers are used to express the rate and energy consumption depending on the amount of load, vehicle speed, and recyclable waste. In addition, a penalty cost of the time windows is considered in both echelons. The models are solved by CPLEX and two meta-heuristic algorithms, gray wolf optimizer (GWO) and tabu search (TS), based on different instance sizes. The results show the efficiency of the proposed algorithms.

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Section: Introductionmentioning

confidence: 99%