We present a method to capture decision maker’s preferences in multiobjective problems and we discuss its use as a base for a decision maker – multiobjective optimization model interface. We illustrate the idea on a small but illustrative numerical example of the airport gate assignment problem.

A Multiobjective optimization approach is used to propose a set of digital controllers for the throttle control benchmark that fulfills its specifications and requirements. The Multiobjective approach allows us to determine the best set of solutions that characterizes the Pareto set, where each solution has a different trade-off between the design objectives.

Our vision is for a seminar that encourages the free exchange of ideas around the organizing subject of learning in MCDM and multiobjective optimization. The following programme provides a skeleton of activities we propose. Participants should suggest amendments to this programme as the week progresses. We encourage the spontaneous formation of working and discussion groups among the participan...

Multiobjective optimization using the conventional weighted aggregation of the objectives method is known to have several drawbacks. In this paper, multiobjective optimization using the weighted aggregation method is approached with the help of evolutionary algorithms. It is shown through a number of test functions that a Pareto front can be achieved from one single run of evolutionary optimiza...

In complex systems like Large-Scale Distributed Systems LSDSs the optimization of resource control is an open issue. The large number of resources and multicriteria optimization requirements make the optimization problem a complex one. The importance of resource control increases with the need of use for industrial process and manufacturing, being a key solution for QoS assuring. This paper pre...

The evolutionary multiobjective optimization technique for analog circuit optimizer is presented in this paper. the technique uses a Parallel Genetic Algorithm(PGA) to identifies multiple “good” solutions from a multiobjective fitness landscape which are tuned using a local hill-climbing algorithm. The PGA is used to provide a nature niching mechanism that has considerable computational advanta...

We propose an extension of Newton’s Method for unconstrained multiobjective optimization (multicriteria optimization). The method does not scalarize the original vector optimization problem, i.e. we do not make use of any of the classical techniques that transform a multiobjective problem into a family of standard optimization problems. Neither ordering information nor weighting factors for the...

In this paper, we modify the general-purpose heuristic method called extremal optimization. We compare our results with the results of Boettcher and Percus [1]. Then, some multiobjective optimization problems are solved by using methods motivated by the immune system.