Many real world problems can be expressed as optimisation problems. Solving such problems means to find, among all possible solutions, the one that maximises an evaluation function. One approach to solve it is to use an informed search strategy. The ...

One of the major operators of Bacterial Foraging Optimization Algorithm (BFOA) is the reproduction phenomenon of virtual bacteria each of which models one trial solution of the optimization problem. During reproduction, the least healthier bacteria (...

Linear Ordering Problem (LOP) is a well know optimization problem attractive for its complexity (it is a NP-hard problem), rich collection of testing data and variety of real world applications. In this paper, we investigate the usage and performance of ...

Complexity in real-world problems is often tackled by a divide-and-conquer strategy which consists of breaking down the problem into sub-problems to find local solutions. These solutions are then merged in a bottom-up fashion and optimized to produce ...

Many real world problems can be expressed as optimisation problems. Solving this kind of problems means to find, among all possible solutions, the one that maximises an evaluation function. One approach to solve this kind of problem is to use an ...

This paper presents an original method of permanent magnet motor optimal design developped by both Electrical Engineering and Computer Science laboratories. An Evolutionary Algorithm combining Genetic Algorithms and Multiagent Systems is used. This ...

Meta-heuristics are general frameworks of heuristics methods for solving combinatorial optimization problems, where exploring the exact solutions for these problems becomes very hard due to some limitations like extremely large running time. In this ...

Bacterial Foraging Optimization Algorithm (BFOA) attempts to model the individual and group behavior of E. Coli bacteria as a distributed optimization process. Since its inception, BFOA has been finding many important applications in real-world ...

Peer-to-peer (P2P) topology has a significant influence on the performance, search efficiency and functionality, and scalability of the application. In this paper, we investigate a multi-swarm approach to the problem of Neighbor Selection (NS) in P2P ...

Broadcasting efficiently in a Vehicular Ad hoc Network (VANET) is a hard task to achieve. An efficient communication algorithm must take into account several aspects such as the neighboring density, the size and shape of the network, the use of the ...

In this paper, we propose to solve the hybrid flow shop scheduling problem with multiple criteria, by using an hybrid method. This latter consists on the one hand, to use a meta-heuristic based on ant colony optimization algorithm to generate feasible ...

In this study, we critically analyse and compare performances of several global optimization (GO) approaches with our hybrid GLP_τS method, which uses meta-heuristic rules and a local search in the final stage of finding a global solution. We also ...

Evolutionary multiobjective optimization (EMO) is one of the most active research areas in evolutionary computation. EMO algorithms have been successfully used in various application areas. Among them are multiobjective design of neural networks and ...