O -line routing in backbone communications networks is an important combinatorial optimisation problem. It has three main uses: rst, o -line routing provides reference benchmark results for dynamic (on-line) routing strategies. Second, and more interestingly, o -line routing is becoming more and more investigated and employed in its own right as a way of quickly nding signi cantly improved rout...

We present a multiobjective genetic clustering approach, in which data points are assigned to clusters based on new line symmetry distance. The proposed algorithm is called multiobjective line symmetry based genetic clustering (MOLGC). Two objective functions, first the Davies-Bouldin (DB) index and second the line symmetry distance based objective functions, are used. The proposed algorithm ev...

-This paper presents a multiobjective genetic algorithm (MOGA)to solve the train crew pairing problem in railway companies. The proposed MOGA has several features, such as 1) A permutation-based model is proposed rather than the 0-1 set partition model. 2) Instead of pre-assigning a fixed group number of crewmembers, the proposed method can determine it by performing the evolutionary process. 3...

In this paper, we demonstrate that simple fuzzy rule-based classification systems with high interpretability are obtained through multiobjective genetic rule selection. In our approach, first a prespecified number of candidate fuzzy rules are extracted from numerical data in a heuristic manner using rule evaluation criteria. Then multiobjective genetic rule selection is applied to the extracted...

This paper introduces a bi-objective winner-determination problem and presents a multiobjective genetic algorithm to solve it. The problem examined arises in the procurement of transportation contracts via combinatorial auctions. It is modeled as an extension to the set-covering problem and considers the minimization of the total procurement costs and the maximization of the service-quality lev...

An optimization procedure aimed at the design of multicomponent airfoils for high-lift applications is described. The procedure is based on a multiobjective genetic algorithm; two #ow solvers have been coupled with the genetic algorithm: a viscous}inviscid interaction method, based on an Euler #ow solver and an integral boundary layer routine, and a method based on a full potential #ow solver. ...

In this paper we report the evolution of a feature extraction stage for edge detection using multidimensional multiobjective genetic programming. We have employed training and validation data produced using a realistic model of the imaging physics to evolve an n-to-m mapping which projects the pixel intensities of an n × n image patch into an m-dimensional decision space. The (near-)optimal val...

1 AbstractIn this paper, a new distributed genetic algorithm for multiobjective optimization problems is proposed. In this approach, the island model is used with a distributed genetic algorithm and an operation of sharing for Pareto-optimum solutions is performed with the total population. In multiobjective optimization problems, the Pareto-optimum solutions should be derived for designers. Be...

In this paper, Divided Range MultiObjective Genetic Algorithm (DRMOGA) is proposed. The DRMOGA is a model of genetic algorithm in multi-objective problems for parallel processing. In the DRMOGA, the population of GAs is sorted with respect to the values of the objective function and divided into sub populations. In each sub population, simple GA for multiobjective problems is performed. After s...

This paper considers the Bicriteria Network Design Problem (bNDP) with the two conflicting objectives of minimizing cost and maximizing flow. Network design problems where even one flow measure be maximized, are often NP-hard problems. But, in real-life applications, it is often the case that the network to be built is required to optimize multi-criteria simultaneously. Thus the calculation of ...