In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...

Different class of stakeholders of Computational Grid has their own perspective and preferences, which result in different, often contradictory, criteria for scheduling (main step of grid resource management). To increase the level of satisfaction of different class of stakeholders grid management system must use the scheduling heuristic, which provides compromise solution (i.e. a compromise sc...

Building maintenance management involves decision-making under multiple objectives and uncertainty, in addition to budgetary constraints. This paper presents the development of a multiobjective and stochastic optimization system for maintenance management of roofing systems that integrates stochastic condition assessment and performance prediction models with a multiobjective optimization appro...

We show in this paper that de Bruijn networks, despite providing efficient search while using constant routing table size, as well as simplicity of the understanding and implementation of such networks, are unsuitable where key distribution will be uneven, a realistic scenario for most practical applications. In presence of arbitrarily skewed data distribution, it has only recently been shown t...

We analyze time-costly decision-making in committees by privately informed individuals, such as juries, panels, boards, etc. In the spirit of the Coase Conjecture, we show that the decision is ‘almost instantaneous’ when individuals entertain identical objectives. Delay can only be understood as the outcome of conflicting (biased) objectives.