Fuzzy Mathematical Programming and Self-Adaptive Artificial Fish Swarm Algorithm for Just-in-Time Energy-Aware Flow Shop Scheduling Problem With Outsourcing Option

Flow shop scheduling (FSS) problem constitutes a major part of production planning in every manufacturing organization. It aims at determining the optimal sequence of processing jobs on available machines within a given customer order. In this article, a novel biobjective mixed-integer linear progra...

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Published inIEEE transactions on fuzzy systems Vol. 28; no. 11; pp. 2772 - 2783
Main Authors Babaee Tirkolaee, Erfan, Goli, Alireza, Weber, Gerhard-Wilhelm
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptive algorithms
Algorithms
Energy consumption
Energy management
Energy-conservation
flow shop scheduling (FSS)
Frequency selective surfaces
fuzzy mathematical programming
Genetic algorithms
Integer programming
Job shop scheduling
Linear programming
Mathematical programming
Mixed integer
Multiple objective analysis
Outsourcing
outsourcing option
Parameter sensitivity
Production planning
self-adaptive artificial fish swarm algorithm (SAAFSA)
Sensitivity analysis
Subcontractors
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Abstract Flow shop scheduling (FSS) problem constitutes a major part of production planning in every manufacturing organization. It aims at determining the optimal sequence of processing jobs on available machines within a given customer order. In this article, a novel biobjective mixed-integer linear programming (MILP) model is proposed for FSS with an outsourcing option and just-in-time delivery in order to simultaneously minimize the total cost of the production system and total energy consumption. Each job is considered to be either scheduled in-house or to be outsourced to one of the possible subcontractors. To efficiently solve the problem, a hybrid technique is proposed based on an interactive fuzzy solution technique and a self-adaptive artificial fish swarm algorithm (SAAFSA). The proposed model is treated as a single objective MILP using a multiobjective fuzzy mathematical programming technique based on the ϵ-constraint, and SAAFSA is then applied to provide Pareto optimal solutions. The obtained results demonstrate the usefulness of the suggested methodology and high efficiency of the algorithm in comparison with CPLEX solver in different problem instances. Finally, a sensitivity analysis is implemented on the main parameters to study the behavior of the objectives according to the real-world conditions.
AbstractList Flow shop scheduling (FSS) problem constitutes a major part of production planning in every manufacturing organization. It aims at determining the optimal sequence of processing jobs on available machines within a given customer order. In this article, a novel biobjective mixed-integer linear programming (MILP) model is proposed for FSS with an outsourcing option and just-in-time delivery in order to simultaneously minimize the total cost of the production system and total energy consumption. Each job is considered to be either scheduled in-house or to be outsourced to one of the possible subcontractors. To efficiently solve the problem, a hybrid technique is proposed based on an interactive fuzzy solution technique and a self-adaptive artificial fish swarm algorithm (SAAFSA). The proposed model is treated as a single objective MILP using a multiobjective fuzzy mathematical programming technique based on the ϵ-constraint, and SAAFSA is then applied to provide Pareto optimal solutions. The obtained results demonstrate the usefulness of the suggested methodology and high efficiency of the algorithm in comparison with CPLEX solver in different problem instances. Finally, a sensitivity analysis is implemented on the main parameters to study the behavior of the objectives according to the real-world conditions.
Author Weber, Gerhard-Wilhelm
Babaee Tirkolaee, Erfan
Goli, Alireza
Author_xml – sequence: 1
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  orcidid: 0000-0003-1664-9210
  surname: Babaee Tirkolaee
  fullname: Babaee Tirkolaee, Erfan
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  organization: Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran
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  givenname: Alireza
  surname: Goli
  fullname: Goli, Alireza
  email: a.goli@stu.yazd.ac.ir
  organization: Faculty of Engineering, University of Isfahan, Isfahan, Iran
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  givenname: Gerhard-Wilhelm
  orcidid: 0000-0003-0849-7771
  surname: Weber
  fullname: Weber, Gerhard-Wilhelm
  email: gerhard.weber@put.poznan.pl
  organization: Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland
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Snippet Flow shop scheduling (FSS) problem constitutes a major part of production planning in every manufacturing organization. It aims at determining the optimal...
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SubjectTerms Adaptive algorithms
Algorithms
Energy consumption
Energy management
Energy-conservation
flow shop scheduling (FSS)
Frequency selective surfaces
fuzzy mathematical programming
Genetic algorithms
Integer programming
Job shop scheduling
Linear programming
Mathematical programming
Mixed integer
Multiple objective analysis
Outsourcing
outsourcing option
Parameter sensitivity
Production planning
self-adaptive artificial fish swarm algorithm (SAAFSA)
Sensitivity analysis
Subcontractors
Title Fuzzy Mathematical Programming and Self-Adaptive Artificial Fish Swarm Algorithm for Just-in-Time Energy-Aware Flow Shop Scheduling Problem With Outsourcing Option
URI https://ieeexplore.ieee.org/document/9103073
https://www.proquest.com/docview/2458749928
Volume 28
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