Abstract This paper extends the numerical tuning of tree constants in genetic programming (GP) to multiobjective domain. Using ten real-world benchmark regression datasets and employing Bayesian comparison procedures, we first consider effects feature standardization (without constant tuning) conclude that generally produces lower test errors, but, contrary other recently published work, find m...

A wireless local area network (WLAN) is designed for an IC factory in Hong Kong using the hierarchical genetic algorithm (HGA). The HGA is capable of handling multiobjective functions and discrete constraints. Because of this uniqueness, together with the adopting of a Pareto ranking scheme, a solution can be reached even when skewed multiobjective functions and constraints confinements are bei...

This work deals with the multiobjective robust design optimization of rail vehicle systems moving in short radius curved tracks. Two criteria are considered simultaneously, i.e., safety and comfort. We showed that the deterministic optimal solutions, for the nominal design parameters, can be altered seriously by the design parameters uncertainty. A new algorithm that combines Genetic Algorithms...

In this paper we, present a new heuristic called PowerFM which is a modification of the well-known Fidducia Mattheyeses algorithm for VLSI netlist partitioning. PowerFM considers the minimization of power consumption due to the nets cut. The advantages of using PowerFM as an initial solution generator for other iterative algorithms, in particular Genetic Algorithm (GA) and Tabu Search (TS), for...

This article introduces a genetic programming algorithm for the solution of the multiobjective cellformation problem. This problem is related to the design of a cellular manufacturing production system. A well-known evolutionary multiobjective technique guides the algorithm in its search for the Pareto set of solutions. The framework is tested on an industrial case study taken from the literatu...

This paper presents a multicriterion algorithm for dealing with joint facility location and network design problems, formulated as bi-objective problems. The algorithm is composed of two modules: a multiobjective quasi-Newton algorithm, that is used to find the location of the facilities; and a multiobjective genetic algorithm, which is responsible for finding the efficient topologies. These mo...

This paper presents a multiobjective genetic algorithm which obtains fuzzy rules for subgroup discovery in disjunctive normal form. This kind of fuzzy rules lets us represent knowledge about patterns of interest in an explanatory and understandable form which can be used by the expert. The evolutionary algorithm follows a multiobjective approach in order to optimize in a suitable way the differ...

In this article, we present a method combining a genetic approach with a local search for multiobjective problems. It is an extension of algorithms for the single objective case, with specific mechanisms used to build the Pareto set. The performance of the proposed algorithm is illustrated by experimental results based on a real problem with three objectives. The problem is issued from electric...

The evolutionary multiobjective optimization technique for analog circuit optimizer is presented in this paper. the technique uses a Parallel Genetic Algorithm(PGA) to identifies multiple “good” solutions from a multiobjective fitness landscape which are tuned using a local hill-climbing algorithm. The PGA is used to provide a nature niching mechanism that has considerable computational advanta...