Get Assembly Line Design: The Balancing of Mixed-Model Hybrid PDF

By Brahim Rekiek

ISBN-10: 1846281121

ISBN-13: 9781846281129

Effective meeting line layout is an issue of substantial commercial significance. meeting Line layout can be received by means of technical group of workers operating in layout, making plans and creation departments in in addition to managers in who are looking to examine extra approximately concurrent engineering. This publication may also be bought by means of researchers and postgraduate scholars in mechanical, production or micro-engineering.

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Read or Download Assembly Line Design: The Balancing of Mixed-Model Hybrid Assembly Lines with Genetic Algorithms (Springer Series in Advanced Manufacturing) PDF

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Additional info for Assembly Line Design: The Balancing of Mixed-Model Hybrid Assembly Lines with Genetic Algorithms (Springer Series in Advanced Manufacturing)

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There are many variations of the crossover operator, and the most common ones are the ‘P-point crossover’ and the ‘uniform crossover’ [57]. In the P-point crossover, each parent is divided at P locations into P+1 contiguous sections, numbered 1 through P+1. Two offspring are created by 4 Evolutionary Combinatorial Optimisation 37 exchanging every odd section between the two parents. The uniform crossover can be thought of as P-point crossover, where P+1 is the number of genes in each parent. Therefore, each gene is a section and every section is probabilistically interchanged between the two parents.

At the same time, Fogel et al. [48] introduced evolutionary programming, and Schwefel [149] proposed evolution strategies. The first objective of this chapter is to make the reader familiar with the GA technique by introducing its origin and concepts. 2 System Organisation Search algorithms define a design problem in terms of a search problem where the search space is a space filled with a set of points. Each point in that space defines a solution. The design problem is then transformed into the problem of searching for the best solutions somewhere in the space of valid ones.

The second step of the evolution cycle is the recombination which takes the responsibility of introducing new individuals into the population. This is done by the genetic operators: crossover, mutation and inversion. Thus, together, crossover, mutation and inversion allow GAs to discover fit, short and low-order schemata over time. Crossover The most popular mechanisim is where two individuals are selected and are crossed over in order to produce offspring. The aim of crossover is to produce new solutions in regions of search space where successful ones have already been found.

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Assembly Line Design: The Balancing of Mixed-Model Hybrid Assembly Lines with Genetic Algorithms (Springer Series in Advanced Manufacturing) by Brahim Rekiek


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