Multi-objective optimization for energy-efficient flow shop scheduling problem with blocking and collision-free transportation constraints

In this paper, the energy-efficient flow shop scheduling problem with blocking and collision-free transportation constraints (EFSP-BCFT) with sequence dependent setup times (SDST), scheduling of automated guided vehicles (AGV), transportation speed control and battery management is investigated. An...

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Bibliographic Details
Published in:Applied soft computing Vol. 148; p. 110884
Main Authors: Boufellouh, Radhwane, Belkaid, Fayçal
Format: Journal Article
Language:English
Published: Elsevier B.V 01.11.2023
Subjects:
Automatic guided vehicle
Energy-efficient flow shop scheduling
Enhanced multi-objective ant colony algorithm
Total energy consumption
Transportation speed
Transportation speed
Enhanced multi-objective ant colony algorithm
Total energy consumption
Energy-efficient flow shop scheduling
Automatic guided vehicle
ISSN:1568-4946, 1872-9681
Online Access:Get full text
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Summary:In this paper, the energy-efficient flow shop scheduling problem with blocking and collision-free transportation constraints (EFSP-BCFT) with sequence dependent setup times (SDST), scheduling of automated guided vehicles (AGV), transportation speed control and battery management is investigated. An enhanced multi-objective ant colony algorithm (EMOACA) is developed to minimize makespan and total energy consumption simultaneously. Several enhancement techniques including a novel low-high resolution search strategy, an effective AGV dispatching heuristic information and critical-path-based energy reduction improvement procedure are proposed. Extensive experiments spanning various scenarios of the problem are conducted and computational results demonstrate the effectiveness of the proposed method and enhancements to obtain high quality solutions compared to standard and state- of-the-art metaheuristics. The results also showcase the significance of considering transportation speed control, battery management and AGV idle power consumption in the modelling of the problem where better system performance can be achieved both in terms of shorter schedules and smoother transportation flow. •EFSP-BCFT is investigated to simultaneously optimize makespan and total energy consumption.•Conflict-free constraints, transportation speed control and battery management of AGVs are considered.•An enhanced algorithm named EMOACA is proposed.•A deep analysis of the different problem characteristics is provided.•The proposed approach is validated through various computational experiments.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2023.110884