We consider a vector minimax Boolean programming problem. The problem consists in finding the set of Pareto optimal solutions. When the problem’s parameters vary then the optimal solution of the problem obtained for some initial parameters may appear non-optimal. We calculate the maximal perturbation of parameters which preseves the optimality of a given solution of the problem. The formula for...

In this paper, we consider the problem of Pareto optimal allocation in a general framework, involving preference functionals defined on a general real vector space. The optimization problem is equivalent to a modified sup-convolution of the different agents’ preference functionals. The results are then applied to a multi-period setting and some further characterization of Pareto optimality for ...

In this paper the authors point out that the Pareto Optimality is unfair, unreasonable and imperfect for Many-objective Optimization Problems (MOPs) underlying the hypothesis that all objectives have equal importance. The key contribution of this paper is the discovery of the new definition of optimality called ε-optimality for MOP that is based on a new conception, so called ε-dominance, which...

Swarm Intelligence (SI) is a relatively new paradigm being applied in a host of research settings to improve the management and control of large numbers of interacting entities such as communication, computer and sensor networks, satellite constellations and more. Attempts to take advantage of this paradigm and mimic the behavior of insect swarms however often lead to many different implementat...

This paper deals with the utilizing of the Bayesian optimization algorithm (BOA) for the Pareto bi-criteria optimization of the 0/1 knapsack problem. The main attention is focused on the incorporation of the Pareto optimality concept into classical structure of the BOA algorithm. We have modified the standard algorithm BOA for one criterion optimization utilizing the known niching techniques to...

In this paper we present a new image thresholding method based on a multiobjective Genetic Algorithm using the Pareto optimality approach. We aim to optimize multiple criteria in order to increase the segmentation quality. Thus, we’ve adapted the well known Non Domination Sorting Genetic Algorithm for this purpose so that it takes into consideration the contribution of the objective functions i...

This paper addresses optimal architectural design using BIM at the design stage. We present a comparative study of the differences between datacentric and process-driven interoperability approaches during the design phases. The authors will elaborate on two approaches, summarize their consequences, and present a real application of the approach using a DAI (Design Analysis Integration) prototyp...

" We show that, in markets with indivisibilities (typified by the Shapley-Scarf housing market), the strict core mechanism is categorically determined by three assumptions: individual rationality, Pareto optimality and strategy-proofness.

We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal) solution preserves optimality was obtained. MSC: 90C29, 90C31

We consider a multiple criterion Boolean programming problem with MINMAX partial criteria. The extreme level of independent perturbations of partial criteria parameters such that efficient (Pareto optimal) solution preserves optimality was obtained. MSC: 90C29, 90C31