Journal ArticleDOI
Performance Improvement of Teaching-Learning-Based Optimisation for Robust Machine Layout Design
TLDR
The development of a computer aided layout designing tool for minimising the total material flow distance under dynamic demand scenario is described and four TLBO modifications for improving its performance are proposed.Abstract:
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.read more
Citations
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Journal ArticleDOI
Facility layout planning. An extended literature review
TL;DR: A scientific literature review about FLP from the operations management perspective is offered, stressing that the generation of layout alternatives was done mainly using mathematical optimisation models, specifically discrete quadratic programming models for similar sized departments, or continuous linear and non-linear mixed integer programming model for different sized departments.
Journal ArticleDOI
Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production
Ágota Bányai,Béla Illés,Elke Glistau,Norge Isaias Coello Machado,Péter Tamás,Faiza Manzoor,Tamás Bányai +6 more
TL;DR: The structure of matrix production as a cyber-physical system focusing on logistics aspects is introduced and a mathematical model of this in-plant supply process is described including extended and real-time optimization from routing, assignment, and scheduling points of view.
Journal ArticleDOI
Performance improvement strategies on Cuckoo Search algorithms for solving the university course timetabling problem
TL;DR: The statistical analysis on the computational results suggested that the proposed algorithms significantly outperformed the conventional CS, Particle Swarm Optimisation (PSO), and hybrid PSO for all problem instances.
Journal ArticleDOI
A TOPSIS-based approach for sustainable layout design: activity relation chart evaluation
TL;DR: The obtained results confirm that the proposed model can assist practitioners in refining their decision processes, particularly in cases where there are many ARC alternatives to be considered, and is beneficial to researchers and practitioners for better understanding the ARC evaluation problem from the perspective of sustainability.
Journal ArticleDOI
Robust machine layout design under dynamic environment: dynamic customer demand and machine maintenance
TL;DR: A robust machine layout design tool that minimises the material flow distance using a Genetic Algorithm (GA), taking into account demand uncertainty and machine maintenance is presented.
References
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Book
Genetic algorithms in search, optimization, and machine learning
TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.
Genetic algorithms in search, optimization and machine learning
TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Journal ArticleDOI
Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems
TL;DR: The effectiveness of the TLBO method is compared with the other population-based optimization algorithms based on the best solution, average solution, convergence rate and computational effort and results show that TLBO is more effective and efficient than the other optimization methods.
Journal ArticleDOI
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
Christian Blum,Andrea Roli +1 more
TL;DR: A survey of the nowadays most important metaheuristics from a conceptual point of view and introduces a framework, that is called the I&D frame, in order to put different intensification and diversification components into relation with each other.
Book
Genetic algorithms and engineering design
光男 玄,Runwei Cheng +1 more
TL;DR: Findings of Genetic Algorithms and Selected Topics in Engineering Design help solve problems in optimization, including Flow-Shop Sequencing Problems, Machine Scheduling Problems, and Facility Layout Design Problems.