The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time
This paper proposes a two-phase hybrid approach for the travelling salesman problem (TSP). The first...
Recently, Genetic Algorithms (GAs) have been investigated as a technique for solving combinatorial o...
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorith...
Background: The Travelling Salesman Problem is an NP-hard problem in combinatorial optimization with...
The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorith...
Abstract The performance of Genetic Algorithms (GA) is affected by various factors such as parameter...
Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Sa...
The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial opt...
We briefly review previous attempts to generate near-optimal solutions of the Traveling Salesman Pro...
One of the challenges in global optimization is to use heuristic techniques to improve the behaviour...
Abstract—Genetic algorithm (GA) is too dependent on the initial population and a lack of local searc...
The generalized traveling salesman problem (GTSP) deals with finding the minimum-cost tour in a clus...
The conventional GA combined with a local search algorithm, such as the 2-OPT, forms a hybrid geneti...
Abstract: Traveling salesman problem is quite known in the field of combinatorial optimization. Thro...
The automatic generation of procedures for combinatorial optimization problems is emerging as a new ...
This paper proposes a two-phase hybrid approach for the travelling salesman problem (TSP). The first...
Recently, Genetic Algorithms (GAs) have been investigated as a technique for solving combinatorial o...
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorith...
Background: The Travelling Salesman Problem is an NP-hard problem in combinatorial optimization with...
The Traveling salesman problem (TSP) is proved to be NP-complete in most cases. The genetic algorith...
Abstract The performance of Genetic Algorithms (GA) is affected by various factors such as parameter...
Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Sa...
The Genetic Algorithm (GA) is one of the most important methods used to solve many combinatorial opt...
We briefly review previous attempts to generate near-optimal solutions of the Traveling Salesman Pro...
One of the challenges in global optimization is to use heuristic techniques to improve the behaviour...
Abstract—Genetic algorithm (GA) is too dependent on the initial population and a lack of local searc...
The generalized traveling salesman problem (GTSP) deals with finding the minimum-cost tour in a clus...
The conventional GA combined with a local search algorithm, such as the 2-OPT, forms a hybrid geneti...
Abstract: Traveling salesman problem is quite known in the field of combinatorial optimization. Thro...
The automatic generation of procedures for combinatorial optimization problems is emerging as a new ...
This paper proposes a two-phase hybrid approach for the travelling salesman problem (TSP). The first...
Recently, Genetic Algorithms (GAs) have been investigated as a technique for solving combinatorial o...
Choosing the correct algorithm to solve a problem still remains an issue 40 years after the Algorith...