A Hyper-Heuristic Algorithm for Time-Dependent Green Location Routing Problem With Time Windows

The Location Routing Problem (LRP), a branch of logistics management, has been addressed in many research papers. However, there are few papers on time-dependent LRP. And only a few of them take fuel consumption into consideration. To reduce the environmental pollution from vehicle emissions and the cost pressure on logistics, a novel model named the time-dependent green location routing problem with time windows (TDGLRP) is developed. Its objective is to minimize costs including opened depot costs, enabled vehicle costs and fuel consumption costs. In TDGLRP the speed and travel times are time-dependent function. A hyper-heuristic algorithm (HH) that consists of two levels, high-level heuristics (HLHs) and low-level heuristics (LLHs), is proposed to solve the TDLGRP. The Tabu Search (TS) algorithm is taken as the high-level selection mechanism, and the Greedy algorithm is taken as the acceptance mechanism. With reference to the Solomon benchmarks, we design a series of TDGLRP instances with 100 client nodes, and analyze the impact of client distribution characteristics on the path. Based on the TDGLRP model and HH, the end of the article gives the solution results of a large-scale instances with 1000 nodes.

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