When facing a real world, optimization problems mainly become multiobjective i.e. they have several criteria of excellence. A multi-criteria problem submitted for multi-criteria evaluation is a complex problem, as usually there is no optimal solution, and no alternative is the best one according to all criteria. However, if a metaheuristic algorithm is combined with a Multi-Criteria Decision-Ma...

scheduling for job shop is very important in both fields of production management and combinatorial op-timization. however, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. the combination of several optimization criteria induces additional complexity and new problems. in this paper, we pro...

We propose a general methodology for approximating the Pareto front of multi-criteria optimization problems. Our search-based methodology consists of submitting queries to a constraint solver. Hence, in addition to a set of solutions, we can guarantee bounds on the distance to the actual Pareto front and use this distance to guide the search. Our implementation, which computes and updates the d...

in this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (moso) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. the model was applied to solve the practical m...

In this paper a Population-based Ant Colony Optimization approach is proposed to solve multi-criteria optimization problems where the population of solutions is chosen from the set of all non-dominated solutions found so far. We investigate different maximum sizes for this population. The algorithm employs one pheromone matrix for each type of optimization criterion. The matrices are derived fr...

Multiple criteria optimization seeks to simultaneously optimize two or more objective functions under a set of constraints. It has a great variety of applications, ranging from financial management, energy planning, sustainable development, to aircraft design. Data mining is aim at extracting hidden and useful knowledge from large databases. Major contributors of data mining include machine lea...

In this paper we present a cooperative coevolutive model for the evolution of neural network topology and weights, called MOBNET. MOBNET evolves subcomponents that must be combined in order to form a network, instead of whole networks. The problem of assigning credit to the subcomponents is approached as a multi-objective optimization task. The subcomponents in a cooperative coevolutive model m...