In this paper we introduce a fuzzy based engine for the scheduling problem. We assume that a human planner is unable to determine the weights for a multi-objective system but is able only to compare between pairs of objectives according to a limited vocabulary. We convert this vocabulary to fuzzy terminology and apply a fuzzy based optimum search for a solution to the scheduling problem. We dem...

– The standard multiple criteria optimization starts with an assumption that the criteria are incomparable. However, there are many applications in which the criteria express ideas of allocation of resources meant to achieve some equitable distribution. This paper focuses on solving linear multiple criteria optimization problems with uniform criteria treated in an equitable way. An axiomatic de...

Many relevant industrial optimization tasks feature more than just one quality criterion. State-of-the-art multi-criteria optimization algorithms require a relatively large number of function evaluations (usually more than 10) to approximate Pareto fronts. Due to high cost or time consumption this large amount of function evaluations is not always available. Therefore, it is obvious to combine ...

We elaborate upon new strategies and heuristics for solving multi-criteria optimization problems via Answer Set Programming (ASP). In particular, we conceive a new solving algorithm, based on conflictdriven learning, allowing for non-uniform descents during optimization. We apply these techniques to solve realistic Linux package configuration problems. To this end, we describe the Linux package...

We propose a new framework for multi-criteria optimization in constraint-based temporal reasoning. Motivated by a real-world domain, we augment one of the most expressive current formalisms, the Disjunctive Temporal Problem with Preferences (DTPP), in two crucial ways. First, we model optimality criteria as being attributed to subsets of soft constraints, in contrast to the direct mapping to in...

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...

Ove DITLEVSEN Professor, dr. techn. Department of Structural Engineering Technical University of Denmark DK 2800 Lyngby Ove Ditlevsen, born 1935, got his civil engineering degree 1959, his degree of dr. techn. 1971, both from the Technical University of Denmark. Professor of applied mathematics at the Danish Engineering Academy until 1984. Since then research professor (until 1991) and professo...

This chapter proposes new heuristic algorithms to solve grid scheduling problem. Two heuristic algorithms, based on Ant Colony Optimization and Particle Swarm Optimization are proposed. The optimization criteria, namely, flowtime and makespan are used to measure the quality of grid scheduling algorithm. Using the simulated benchmark instances, the results of different algorithms are analyzed an...