The combination of evolutionary algorithms with local search was named" memetic
algorithms"(MAs)(Moscato, 1989). These methods are inspired by models of natural systems …

This work proposes an evolutionary algorithm, called the heterogeneous selection
evolutionary algorithm (HeSEA), for solving large traveling salesman problems (TSP). The …

In this paper, hybrid ant colony optimization (HAntCO) approach in solving multi-skill
resource-constrained project scheduling problem (MS-RCPSP) has been presented. We …

In this paper we introduce a promising hybridization scheme for a Memetic Algorithm (MA).
Our MA is composed of two optimization processes, a Genetic Algorithm and a Monte Carlo …

Genetic algorithms are different from most other metaheuristics because they exploit three
key ideas:(1) the use of a population of solutions to guide search,(2) the use of crossover …

The multiagent optimization system (MAOS) is a nature-inspired method, which supports
cooperative search by the self-organization of a group of compact agents situated in an …

In this paper, we introduce a new crossover operator for the permutation representation of a
GA. This new operator---Non-Wrapping Order Crossover (NWOX)---is a variation of the well …

In the field of evolutionary algorithms (EAs), many operators have been introduced for the
traveling salesman problem (TSP). Most encoding schemes have various restrictions that …

The bottleneck traveling salesman problem is to find a Hamiltonian circuit that minimizes the
largest cost of any of its arcs in a graph. A simple genetic algorithm (GA) using sequential …

There are many combinatorial optimization problems whose solutions are best represented
by permutations. The classic traveling salesperson seeks an optimal ordering over a set of …