Journal Article10.1023/A:1006529012972
Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators
TL;DR: This paper presents crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation.
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Abstract: This paper is the result of a literature study carried out by the authors. It is a review of the different attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Likewise, we show the experimental results obtained with different standard examples using combination of crossover and mutation operators in relation with path representation.
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Citations
Cooperative Path Planning for Aerial Recovery of a UAV Swarm Using Genetic Algorithm and Homotopic Approach
TL;DR: In this study, the recovery problem of a UAV swarm by a mother aircraft has been investigated and a recovery planning framework is proposed to establish the coupling mechanism between the scheduling and path planning of a multi-UAV aerial recovery.
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A Study of Genetic Algorithms to Solve the School Timetabling Problem
Rushil Raghavjee,Nelishia Pillay +1 more
- 24 Nov 2013
TL;DR: It is revealed that different combinations of low-level construction heuristics, selection methods and genetic operators are needed to produce feasible timetables of good quality for the different school timetabling problems.
13
Genetic Algorithms and the Traveling Salesman Problem a historical Review.
TL;DR: A highly abstracted view on the historical development of Genetic Algorithms for the Traveling Salesman Problem and an outlook to future work in this field is given.
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Collision-free motion planning and scheduling
TL;DR: In this article, the authors present the positioning, motion coordination and test ordering procedures of new testing equipment for printed circuit boards, which consists of four mobile probes whose movements must be coordinated to avoid collisions both with obstacles and with each other.
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Evolutionary memetic algorithms supported by metaheuristic profiling effectively applied to the optimization of discrete routing problems
TL;DR: MHP is applied, using the Excel-VBA platform, to reveal the relative contribution of the nine metaheuristics involved in the routing MA developed here, which incorporates some of the meta heuristics derived from bat-flight principles.
13
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