Immunity Genetic Algorithm Based on Elitist Strategy and Its Application to the TSP Problem

Liang, Yan; Yang, Kongyu

doi:10.1109/ettandgrs.2008.407

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“…Being a global search algorithm, it is capable of producing better solutions in complex situations through chromosome representation, reproduction, crossover, and mutation. The concept of Artificial Immune System (AIS) was improved from GA and was originally proposed by Jerne [26]; it has since been widely studied (e.g., see [26][27][28][29][30][31][32]). In Immune Genetic Algorithm (IGA) approaches, we calculate the affinity between any pairs of strings.…”

Section: Introductionmentioning

confidence: 99%

Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

2013

Abstract and Applied Analysis

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We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R) machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

2013

Abstract and Applied Analysis

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An improvement of partheno-genetic algorithm to solve multiple travelling salesmen problem

Zhou

Song

2016

2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)

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Immunity Genetic Algorithm Based on Elitist Strategy and Its Application to the TSP Problem

Cited by 2 publications

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Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

An improvement of partheno-genetic algorithm to solve multiple travelling salesmen problem

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