• Aucun résultat trouvé

An Algorithm for Approximating High-Order Pareto Frontier in Multiobjective Integer Linear Problems

N/A
N/A
Protected

Academic year: 2022

Partager "An Algorithm for Approximating High-Order Pareto Frontier in Multiobjective Integer Linear Problems"

Copied!
1
0
0

Texte intégral

(1)

Environmental Decision Making

The 21st International Conference on Multiple Criteria Decision Making 13–17 June 2011, Jyväskylä, Finland

Invited Session

An Algorithm for Approximating High-Order Pareto Frontier in Multiobjective Integer Linear Problems

Vladimir Bushenkov University of Evora, CIMA-UE [email protected]

Manuela Fernandes

Instituto Politecnico de Tomar, CIMA-UE [email protected]

An algorithm for approximating the Pareto frontier (PF) in multiobjective integer linear problems is presented.

As known, the feasible set in the objective space (FSOS) for an integer linear programming problem is not convex and only a few points of its Pareto frontier (so called supported points) can be found when constructing its convex hull. To get these points at the fisrt iteration of our algorithm we construct the convex Edgeworth-Pareto hull (CEPH) of the FSOC, i.e. a broader convex set that has the same Pareto frontier.

The algorithm for constructing CEPH is more simple then one for constructing convex hull. It gives the result in the form of both a set of vertices and a system of linear inequalities. Using this information we can specify an unexplored region in the objective space which contains all not found yet Pareto frontier’s points. This region is restricted by the CEPH’s Pareto frontier and the Pareto frontier of the union of cones dominated by corresponding CEPH’s vertices. It can be easily vizualized on computer display.

At each iteration, one unexplored subregion is selected to construct its partial CEPH. To formulate this subproblem, vertices and hyperplanes of CEPHs calculated at the previous iterations are used. As a result, new PF’s points for the initial problem can be found and the unexplored area is reduced.

The proposed algorithm can be apllied for approximating Pareto frontier in the criteria space till 4-5 dimen- sions. It can be useful for Decision Support Systems in such areas as forest planning and management, water resources management and etc.

References

Lotov A., Bushenkov V., Kamenev G. Interactive Decision Maps. Approximation and Visualization of Pareto Frontier. Kluwer Academic Publishers, 2004.

Presenting author

Références

Documents relatifs

For both unweighted and weighted instances, we display the average running time of the model, the average relative gap and the number of instances out of five that are solved within

Linear programming (LP) solvers come from the tradition of optimization, and are designed to find feasible solutions that are optimal with respect to some optimization

To remedy this situation, we present an interac- tive interior point algorithm for determining a best compromise solution to a multiobjective linear pro- gramming problem (MOLP)

The convergence to the Pareto frontier and the distribution of solutions obtained by LGP, ParEGO and NSGA II for the test function DTLZ1a is depicted in Fig.. Different sizes

In this work, we propose a formulation based on an upper bound of the number of nodes in the BP tree, and we provide an integer programming model (IP) for its exact solution....

Keywords periodic scheduling, resource-constrained modulo scheduling, in- teger linear programming formulations, lower bounds, column generation..

However, for hard instances with a considerable number of disjunctions, such as the instances with 10 tasks and 3 machines, the execution times of the MILP rocket up and it is

- Support of pattern set. The area of a pattern set was studied in the context of large tile mining [6].. Discrim- inative measures are typically defined by comparing the number