Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem
نویسندگان
چکیده
منابع مشابه
Comparative Analysis of Evolutionary Algorithms for Multi-Objective Travelling Salesman Problem
The Evolutionary Computation has grown much in last few years. Inspired by biological evolution, this field is used to solve NP-hard optimization problems to come up with best solution. TSP is most popular and complex problem used to evaluate different algorithms. In this paper, we have conducted a comparative analysis between NSGA-II, NSGA-III, SPEA-2, MOEA/D and VEGA to find out which algorit...
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The Travelling Salesman Problem is a well known problem which has becomea comparison benchmark test for different computational methods. Its solution is computationally difficult, although the problem is easily expressed. TSP is one of the most famous combinatorial optimization (CO) problems and which has wide application background. The aim of our work is to compare existing algorithms that ar...
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Genetic algorithms (GAs) were developed as problem independent search algorithms (Goldberg, 1989; Holland, 1975; Man et al., 1999), which simulate the biological evolution to search for an optimal solution to a problem. Figure 1(a) shows the main processes of genetic algorithms. When developing a genetic algorithm, we analyze the properties of the problem and determine the “gene encoding” polic...
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In the real world, it is common to face optimization problems that have two or more objectives that must be optimized at the same time, that are typically explained in different units, and are in conflict with one another. This paper presents a hybrid structure that combines set of experience knowledge structures (SOEKS) and evolutionary algorithms, NSGA-II (Non-dominated Sorting Genetic Algori...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2018
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2018.090251