Development of Island Model Genetic Algorithms with Different Genetic Operators

Outfitting is a critical stage in the shipbuilding process. Within the outfitting, the construction of pipe systems is a phase that has a significant effect on time and cost. While cutting the pipes required for the pipe systems in shipyards, the cutting process is usually performed randomly. This can result in large amounts of trim losses. In this paper, we present an approach to minimize these losses. With the proposed method it is aimed to base the pipe cutting process on a specific systematic. To solve this problem, Genetic Algorithms (GA), which gives successful results in solving many problems in the literature, have been used. Different types of genetic operators have been used to investigate the search space of the problem well. The results obtained have proven the effectiveness of the proposed approach.

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Assembly Planning: A Genetic Approach

Volume 2: 24th Design Automation Conference ◽

10.1115/detc98/dac-5798 ◽

1998 ◽

Author(s):

Shiang-Fong Chen

Keyword(s):

Genetic Algorithms ◽

Fitness Function ◽

Assembly Planning ◽

Genetic Approach ◽

Genetic Operators ◽

Complex Problems ◽

All Solutions ◽

Assembly Problem ◽

Optimal Assembly

Abstract The difficulty of an assembly problem is the inherent complexity of possible solutions. If the most suitable plan is selected after all solutions are found, it will be very time consuming and unrealistic. Motivated by the success of genetic algorithms (GAs) in solving combinatorial and complex problems by examining a small number of possible candidate solutions, GAs are employed to find a near-optimal assembly plan for a general environment. Five genetic operators are used: tree crossover, tree mutation, cut-and-paste, break-and-joint, and reproduction. The fitness function can adapt to different criteria easily. This assembly planner can help an inexperienced technician to find a good solution efficiently. The algorithm has been fully implemented. One example product is given to show the applications and results.

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A GENETIC BASED TECHNIQUE FOR THE DETERMINATION OF POWER SYSTEM TOPOLOGICAL OBSERVABILITY

International Journal of Computing ◽

10.47839/ijc.2.2.199 ◽

2014 ◽

pp. 16-21

Author(s):

S. Vazquez-Rodriguez ◽

R. J. Duro

Keyword(s):

Genetic Algorithms ◽

Power Systems ◽

Power System ◽

Spanning Tree ◽

Point Of View ◽

Genetic Operators ◽

Building Process ◽

Phenotype Transformation

In this paper we have addressed the problem of observability of power systems from the point of view of topological observability and using genetic algorithms for its determination. The objective is to find a way to determine if a system is observable by establishing if a spanning tree of the system that verifies certain properties with regards to the use of available measurements can be obtained. To this end we have developed a genotype-phenotype transformation scheme for genetic algorithms that permits using very simple genetic operators over integer based chromosomes which after a building process can become very complex trees. The procedure was successfully applied to standard benchmark systems and we present some results for one of them.

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