A multi-objective cooperative coevolutionary algorithm for solving the flexible job shop scheduling problem with variable processing speeds and automated guided vehicles
LIU Chao
HAN Yuyan
YANG Xiaoyu
LI Zhen
WANG Yanan
WANG Xu
Abstract：For the multi-objective Flexible Job Shop Scheduling Problem with Automated Guided Vehicles(FJSP-AGVs)and variable processing speed constraints,a mixed integer linear programming(MILP)model is first designed by using a position-based modeling approach,with the objectives of minimizing makespan and total energy consumption(TEC).Then decomposed the FJSP-AGVs problem into four in-terrelated subproblems according to its characteristics:operation sequencing,machine allocation,process-ing speed settings,and automated guided vehicle allocation.To address these four subproblems,we pro-posed a multi-objective cooperative coevolutionary algorithm(MOCEA).In the MOCEA,two collabora-tive evolution strategies based on the critical path are used to promote information exchange between dif-ferent populations,and a strategy to reduce the processing speed of operations on non-critical paths is em-ployed to further optimize the total energy consumption.Finally,experiments were conducted to validate the effectiveness of the proposed MOCEA.
Keywords：flexible job shop schedulingautomated guided vehiclesvariable processing speedsmulti-ob-jectivecooperative coevolutionary
Publication Date：2025-06-25
Online Publishing Date：2026-08-28(First online date of this platform, not the publication date of the document)
Pages：16( 317-332 )