关键词: 选址&mdash, 路径问题, 同时取送货, 低碳物流, 超启发式算法, 量子选择策略

Abstract: Aiming at reducing the carbon emission of vehicles,the Location-Routing Problem with Simultaneous Pickup and Delivery (LRPSPD) model by taking minimum carbon emission as objective was defined,which was tackled by Quantum-inspired Hyper-Heuristic (QHH).In framework of QHH,the quantum Q-gate mechanism based sliding windows was developed as the hyper-level learning strategy to timely manipulate and track the recent performance of Low-Level Heuristics (LLH) for pinpointing the appropriate operators,which was utilized to implement a sort of simple operators such as ‘shift’ and ‘swap’.Moreover,for reducing the computational burden,a solution representation and LLHs were designed to guarantee feasibility of solutions and avoid the use of repair methods to restore feasibility,and a fast solution evaluation technique was developed.Simulation results and comparisons showed that the proposed algorithms were effective,and provided promising results for different scales instances within reasonable computing time.

Key words: location-routing problem, simultaneous pickup and delivery, low-carbon logistics, hyper-heuristics algorithm, quantum-inspired strategy