As an intelligent search optimization technique, genetic algorithm (GA) is an important
approach for non-deterministic polynomial (NP-hard) and complex nature optimization …

The travelling salesman problem (TSP) is a classic problem of combinatorial optimization
and has applications in planning, scheduling, and searching in many scientific and …

Bu çalışmada, NP-zor problem sınıfından olan gezgin satıcı probleminin (GSP), stokastik
optimizasyon tekniklerinin en genel sınıfı olan metasezgisel yöntemlerle çözümü ele …

This article deals with a performance evaluation of particle swarm optimization (PSO) and
genetic algorithms (GA) for traveling salesman problem (TSP). This problem is known to be …

This work shows improvement with a modified form of the existing partially-mapped
crossover operator for the traveling salesman problem. This novel crossover approach has …

The Genetic Algorithm (GA) was developed as a search engine for difficult non-deterministic
polynomial optimization problems. However, it suffers from internal weaknesses, such as …

The research objective is to find a balance between premature convergence and population
diversity with respect to genetic algorithms (GAs). We propose a new selection scheme …

As an intelligent search technique, genetic algorithm (GA) is a key member of optimization
research methods. Motivated by the ability of GA in resolving complex and nondeterministic …

The development of modern information technologies and artificial intelligence systems has
led to the development of non-traditional methods for solving problems. Metaheuristic …

The logistic sector raises a number of highly challenging problems. Probably one of the most
important ones is the shipping planning, ie plan the routes that the shippers have to follow to …