This paper presents an effective approach (EXTRACOL) to coloring large graphs. The proposed approach uses a preprocessing method to extract large independent sets from the graph and a memetic algorithm to color the residual graph. Each preprocessing application identifies, with a dedicated tabu search algorithm, a number of pairwise disjoint independent sets of a given size in order to maximize...

Nowadays, large scale optimisation problems arise as a very interesting field of research, because they appear in many real-world problems (bio-computing, data mining, etc.). Thus, scalability becomes an essential requirement for modern optimisation algorithms. In a previous work, we presented memetic algorithms based on local search chains. Local search chain concerns the idea that, at one sta...

the bi-objective warehouse problem in a crisp environment is often not eective in dealing with the imprecision or vagueness in the values of the problem parameters. to deal with such situations, several researchers have proposed that the parameters be represented as fuzzy numbers. we describe a new algorithm for fuzzy bi-objective warehouse problem using a ranking function followed by an applic...

In this paper we regard a break scheduling problem originating in the area of supervision personnel. This complex task requires the assignment of several breaks per shift, satisfying various constraints reflecting labour rules, staffing requirements and ergonomic criteria. To solve this problem we propose a memetic algorithm combining a genetic algorithm and a local search procedure. We evaluat...

This article explores coordinated scheduling problem arising in steelmaking and multi-refining operations. Jobs are first processed in converters and then transported downstream to be processed in refining furnaces in which two different transporters are employed in tandem at the stage of transportation. There exist multi-refining jobs. The objective is to minimize the maximum completion time s...

Memetic algorithms(MAs) represent one of the promising areas of evolutionary algorithms. However, there are many issues to be solved to design a robust MA. In this paper, we introduce an adaptive memetic algorithm, named GADEDHC, which combines a genetic algorithm and a differential evolution algorithm as global search methods with a directional hill climbing algorithm as local search method. I...

The minimum conductance problem is an NP-hard graph partitioning problem. Apart from the search for bottlenecks in complex networks, the problem is very closely related to the popular area of network community detection. In this paper, we tackle the minimum conductance problem as a pseudo-Boolean optimisation problem and propose a memetic algorithm to solve it. An efficient local search strateg...

Fuzzy cognitive maps constitute a neuro-fuzzy modeling methodology that can simulate complex systems accurately. Although their configuration is defined by experts, learning schemes based on evolutionary and swarm intelligence algorithms have been employed for improving their efficiency and effectiveness. This paper comprises an extensive study of the recently proposed swarm intelligence memeti...

With the fast evolution of real time and multimedia applications, some quality of service (QoS) constraints need to be guaranteed in the underlying network. In this paper, we present a new method for least-cost QoS multicast routing problem based on genetic algorithm and tabu search. This problem has been proven to be NP-complete. The proposed genetic tabu search algorithm (GTS) combine Genetic...

The clustering problem under the criterion of minimum sum of squares is a non-convex and non-linear program, which possesses many locally optimal values, resulting that its solution often falls into these trap and therefore cannot converge to global optima solution. In this paper, an efficient hybrid optimization algorithm is developed for solving this problem, called Tabu-KM. It gathers the op...