scholarly journals Solving the Manufacturing Cell Design Problem through Binary Cat Swarm Optimization with Dynamic Mixture Ratios

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Angelo Aste Toledo ◽  
Hanns de la Fuente-Mella ◽  
Carlos Castro ◽  
...  
Keyword(s):  
Design Problem ◽  
Search Algorithm ◽  
Production Plant ◽  
Cell Design ◽  
Swarm Optimization ◽  
Mixture Ratio ◽  
Manufacturing Cell ◽  
Cat Swarm Optimization ◽  
Autonomous Search ◽  
Behavior Of Cats

In this research, we present a Binary Cat Swarm Optimization for solving the Manufacturing Cell Design Problem (MCDP). This problem divides an industrial production plant into a certain number of cells. Each cell contains machines with similar types of processes or part families. The goal is to identify a cell organization in such a way that the transportation of the different parts between cells is minimized. The organization of these cells is performed through Cat Swarm Optimization, which is a recent swarm metaheuristic technique based on the behavior of cats. In that technique, cats have two modes of behavior: seeking mode and tracing mode, selected from a mixture ratio. For experimental purposes, a version of the Autonomous Search algorithm was developed with dynamic mixture ratios. The experimental results for both normal Binary Cat Swarm Optimization (BCSO) and Autonomous Search BCSO reach all global optimums, both for a set of 90 instances with known optima, and for a set of 35 new instances with 13 known optima.

scholarly journals Solving the Manufacturing Cell Design Problem Using Human Behavior-Based Algorithm Supported by Autonomous Search

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 132228-132239 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Francisco Gonzalez ◽  
Emanuel Vega ◽  
Carlos Castro ◽  
...  
Keyword(s):  
Human Behavior ◽  
Design Problem ◽  
Cell Design ◽  
Manufacturing Cell ◽  
Autonomous Search ◽  
Behavior Based

scholarly journals Solving the Manufacturing Cell Design Problem through an Autonomous Water Cycle Algorithm

2019 ◽  
Vol 9 (22) ◽  
pp. 4736 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Jose M. Lanza-Gutierrez ◽  
Rodrigo Olivares ◽  
Pablo Camacho ◽  
...  
Keyword(s):  
Design Problem ◽  
Optimization Problems ◽  
Water Cycle ◽  
Search Space ◽  
Cell Design ◽  
Optimal Solutions ◽  
Simple Task ◽  
Manufacturing Cell ◽  
Parameter Configuration ◽  
Problem Solvers

Metaheuristics are multi-purpose problem solvers devoted to particularly tackle large instances of complex optimization problems. However, in spite of the relevance of metaheuristics in the optimization world, their proper design and implementation to reach optimal solutions is not a simple task. Metaheuristics require an initial parameter configuration, which is dramatically relevant for the efficient exploration and exploitation of the search space, and therefore to the effective finding of high-quality solutions. In this paper, the authors propose a variation of the water cycle inspired metaheuristic capable of automatically adjusting its parameter by using the autonomous search paradigm. The goal of our proposal is to explore and to exploit promising regions of the search space to rapidly converge to optimal solutions. To validate the proposal, we tested 160 instances of the manufacturing cell design problem, which is a relevant problem for the industry, whose objective is to minimize the number of movements and exchanges of parts between organizational elements called cells. As a result of the experimental analysis, the authors checked that the proposal performs similarly to the default approach, but without being specifically configured for solving the problem.

A one-step tabu search algorithm for manufacturing cell design

1999 ◽  
Vol 50 (5) ◽  
pp. 509-516 ◽  
Author(s):  
S Lozano ◽  
B Adenso-Díaz ◽  
I Eguia ◽  
L Onieva
Keyword(s):  
Tabu Search ◽  
Search Algorithm ◽  
Tabu Search Algorithm ◽  
Cell Design ◽  
Manufacturing Cell ◽  
One Step

Applying an Electromagnetism-Like Algorithm for Solving the Manufacturing Cell Design Problem

2017 ◽  
pp. 37-61
Author(s):  
Jose M. Lanza-Gutierrez ◽  
Ricardo Soto ◽  
Broderick Crawford ◽  
Juan A. Gomez-Pulido ◽  
Nicolas Fernandez ◽  
...  
Keyword(s):  
Design Problem ◽  
Manufacturing Industry ◽  
Group Technology ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Cell Design ◽  
Manufacturing Cell ◽  
Great Consideration ◽  
Np Hard Problem ◽  
Continuous Optimization Problems

Group technology has acquired a great consideration in the last years. This technique allows including the advantages of serial production to any manufacturing industry by dividing a manufacturing plant into a set of machine-part cells. The identification and formation of the cells are known as the Manufacturing Cell Design Problem (MCDP), which is an NP-hard problem. In this paper, the authors propose to solve the problem through a swarm intelligence metaheuristic called ElectroMagnetism-like (EM-like) algorithm, which is inspired by the attraction-repulsion mechanism of particles in the context of the electromagnetic theory. The original EM-like algorithm was designed for solving continuous optimization problems, while the MCDP is usually formulated by assuming a binary approach. Hence, the authors propose an adaptation of this algorithm for addressing the problem. Such adaptation is applied for solving a freely available dataset of the MCDP, obtaining competitive results compared to recent approaches.

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