Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design

•Application of TLBO to solve MLD problems using robust approach is firstly reported.•Superiority of TLBO modifications has been proposed and demonstrated in this work.•Benchmarking datasets used in the computational experiments are provided.•Comprehensive literature review on metaheuristics applied...

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Vydáno v:Expert systems with applications Ročník 98; s. 129 - 152
Hlavní autoři: Vitayasak, Srisatja, Pongcharoen, Pupong
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Ltd 15.05.2018
Elsevier BV
Témata:
Computational intelligence
Demand
Design optimization
Dynamic demand
Facility layout
Heuristic
Learning
Logistics
Manufacturing
Optimization
Parameter modification
Productivity
Robust design
Statistical analysis
Teachers
Teaching
Teaching machines
Teaching-Learning-Based Optimisation
Uncertainty
Variation
Dynamic demand
Teaching-Learning-Based Optimisation
Facility layout
Computational intelligence
Robust design
ISSN:0957-4174, 1873-6793
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Abstract •Application of TLBO to solve MLD problems using robust approach is firstly reported.•Superiority of TLBO modifications has been proposed and demonstrated in this work.•Benchmarking datasets used in the computational experiments are provided.•Comprehensive literature review on metaheuristics applied to solve MLD is presented.•Pseudo codes and mechanisms of the proposed methods are illustrated using figures. Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various optimisation problems. However, TLBO has not been academically reported for solving the robust machine layout design (MLD) problems with dynamic demand. Considering internal logistics activities, shortening material flow distance within a manufacturing area can lead to efficient productivity and a decrease in related costs. The robust machine layout is concerned with determining the efficient arrangement of machines/facilities located on a manufacturing shop floor under future demand fluctuation. A robust designed layout is essential for a company to maintain a high productivity rate through multiple time-periods of demand uncertainty with minimum effects related to the re-layout time and cost, manufacturing disruption, and the movement of monument machines. The objectives of this paper were to: i) describe the development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario, ii) investigate the appropriate setting of TLBO parameters, and iii) propose four TLBO modifications for improving its performance. The modified TLBOs were inspired by multiple teachers with two types of classes and two approaches to teacher selection. The numerical experiments were designed and conducted using eleven MLD benchmarking datasets. Statistical analyses on the experimental results showed a superior performance for the proposed modifications.
AbstractList Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various optimisation problems. However, TLBO has not been academically reported for solving the robust machine layout design (MLD) problems with dynamic demand. Considering internal logistics activities, shortening material flow distance within a manufacturing area can lead to efficient productivity and a decrease in related costs. The robust machine layout is concerned with determining the efficient arrangement of machines/facilities located on a manufacturing shop floor under future demand fluctuation. A robust designed layout is essential for a company to maintain a high productivity rate through multiple time-periods of demand uncertainty with minimum effects related to the re-layout time and cost, manufacturing disruption, and the movement of monument machines. The objectives of this paper were to: i) describe the development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario, ii) investigate the appropriate setting of TLBO parameters, and iii) propose four TLBO modifications for improving its performance. The modified TLBOs were inspired by multiple teachers with two types of classes and two approaches to teacher selection. The numerical experiments were designed and conducted using eleven MLD benchmarking datasets. Statistical analyses on the experimental results showed a superior performance for the proposed modifications.
•Application of TLBO to solve MLD problems using robust approach is firstly reported.•Superiority of TLBO modifications has been proposed and demonstrated in this work.•Benchmarking datasets used in the computational experiments are provided.•Comprehensive literature review on metaheuristics applied to solve MLD is presented.•Pseudo codes and mechanisms of the proposed methods are illustrated using figures. Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various optimisation problems. However, TLBO has not been academically reported for solving the robust machine layout design (MLD) problems with dynamic demand. Considering internal logistics activities, shortening material flow distance within a manufacturing area can lead to efficient productivity and a decrease in related costs. The robust machine layout is concerned with determining the efficient arrangement of machines/facilities located on a manufacturing shop floor under future demand fluctuation. A robust designed layout is essential for a company to maintain a high productivity rate through multiple time-periods of demand uncertainty with minimum effects related to the re-layout time and cost, manufacturing disruption, and the movement of monument machines. The objectives of this paper were to: i) describe the development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario, ii) investigate the appropriate setting of TLBO parameters, and iii) propose four TLBO modifications for improving its performance. The modified TLBOs were inspired by multiple teachers with two types of classes and two approaches to teacher selection. The numerical experiments were designed and conducted using eleven MLD benchmarking datasets. Statistical analyses on the experimental results showed a superior performance for the proposed modifications.
Author Vitayasak, Srisatja
Pongcharoen, Pupong
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  givenname: Pupong
  surname: Pongcharoen
  fullname: Pongcharoen, Pupong
  email: pupongp@nu.ac.th
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Keywords Dynamic demand
Teaching-Learning-Based Optimisation
Facility layout
Computational intelligence
Robust design
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Snippet •Application of TLBO to solve MLD problems using robust approach is firstly reported.•Superiority of TLBO modifications has been proposed and demonstrated in...
Teaching-Learning-Based Optimisation (TLBO) is one of the more recently developed metaheuristics and has been successfully applied to solve various...
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StartPage 129
SubjectTerms Computational intelligence
Demand
Design optimization
Dynamic demand
Facility layout
Heuristic
Learning
Logistics
Manufacturing
Optimization
Parameter modification
Productivity
Robust design
Statistical analysis
Teachers
Teaching
Teaching machines
Teaching-Learning-Based Optimisation
Uncertainty
Variation
Title Performance improvement of Teaching-Learning-Based Optimisation for robust machine layout design
URI https://dx.doi.org/10.1016/j.eswa.2018.01.005
https://www.proquest.com/docview/2029675386
Volume 98
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