By Brahim Rekiek

Effective meeting line layout is an issue of substantial commercial value. meeting Line layout can be obtained 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 study extra approximately concurrent engineering. This ebook may also be bought by means of researchers and postgraduate scholars in mechanical, production or micro-engineering.

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

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The set of individuals (solutions, chromosomes) of each generation is called a population. Chromosomes are characterised by their fitness and evolve through successive iterations (generations). A population of solutions is maintained and the evolution plays the role of adaptation of a population to its environment. This adaptation causes the creation of individuals of increasingly higher ‘fitness’. The best solutions are favoured for reproduction every generation and the offspring are then generated from these fit parents using crossover and mutation.

4 Landscapes and Fitness GAs work on a population of candidate solutions using an objective function. Applying a fitness function to each one of these chromosomes permits to measure the quality of the solution performance. A fitness landscape is a set of points in n-dimension space (hyper-surface) obtained by applying the fitness function to every point in the search space. To optimise a function efficiently, the fitness function must be clearly defined and higher fitness individuals must be explicitly promoted.

4 Landscapes and Fitness GAs work on a population of candidate solutions using an objective function. Applying a fitness function to each one of these chromosomes permits to measure the quality of the solution performance. A fitness landscape is a set of points in n-dimension space (hyper-surface) obtained by applying the fitness function to every point in the search space. To optimise a function efficiently, the fitness function must be clearly defined and higher fitness individuals must be explicitly promoted.

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