Title: Research on multi-objective network optimisation of power material distribution based on the improved ε constraint method

Authors: Guanghui Wang; Yumin Li

Addresses: School of Management, Zhengzhou University, Power Dispatching Control Center, State Grid Qinghai Electric Power Company, Room 1312, Building 13, Qianheyuan, Power Community, Haihu New District, Xining City, Qinghai Province, 810008, China ' School of Management, Zhengzhou University, Family College of Zhengzhou University, No. 100, Science Avenue, High Tech Zone, Zhengzhou City, Henan Province, 450066, China

Abstract: Aiming at the multi-objective distribution path optimisation of power materials, a multi-objective distribution planning system based on the improved ε constraint algorithm is designed. Then a local power material transportation example in China is selected to simulate and test the system. The results show that the optimal solution routes obtained by the system and the planning system based on the naïve ε constraint algorithm are completely consistent except for the material demand node j5, j7, j8 . At the same time, the average total transportation time and average total transportation cost of the system within ε3 calculation accuracy are 386.55 min and 283.06 k$ respectively, which are 4.62%, 9.41%, 6.33% and 1.56%, 6.98%, 3.45% less than the corresponding data of the optimal solution of the system based on the naïve ε constraint algorithm, particle swarm optimisation algorithm and fast RCNN algorithm, respectively. The data show that the algorithm can shorten the time and cost of transportation tasks, and the planning effect is better.

Keywords: ε constraint method; electric power materials; multi-objective planning; transportation route; cost control.

DOI: 10.1504/IJCSM.2022.128192

International Journal of Computing Science and Mathematics, 2022 Vol.16 No.3, pp.225 - 238

Received: 24 Nov 2021
Received in revised form: 23 Aug 2022
Accepted: 23 Aug 2022

Published online: 11 Jan 2023 *

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