An IWOA for multi-objective optimization scheduling of AGV flexible job shop

doi:10.16731/j.cnki.1671-3133.2024.07.003

Abstract

Abstract: Aiming at the problem of Automated Guided Vehicle (AGV) scheduling in flexible job shop,based on the sustainable perspective,considering the problem of workshop energy consumption,under the condition of the number of machines and AVG,a sustainable flexible job shop scheduling model is constructed with the optimization objectives of minimizing the maximum completion time,workshop energy consumption and the number of AGV used.Firstly,an Improved Whale Optimization Algorithm (IWOA) was designed,which introduced a nonlinear convergence factor and adaptive inertia weight on the basis of the standard whale optimization algorithm to improve the search ability and convergence speed of the algorithm.Secondly,the fuzzy membership theory was used to construct the loss function to obtain the optimal compromise solution of the multi-objective model. Finally,the performance of the algorithm was verified based on examples. The experimental results show that IWOA shows good effects in solving instances of different sizes,which provides an effective practical way for solving the sustainable flexible job shop optimization scheduling with AGV transportation.

Key words: flexible job shop, sustainable, multi-objective optimization scheduling, Improved Whale Optimization Algorithm (IWOA), fuzzy membership

CLC Number:

TH165
TP18

WANG Yun, MA Rong, TANG Siyuan. An IWOA for multi-objective optimization scheduling of AGV flexible job shop[J]. Modern Manufacturing Engineering, 2024, 526(7): 17-25.

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