Solution of real world problems have to deal with some uncertainties. This is particularly true for the planning of services whose requests are unknown a priori. Several approaches for solving stochastic problems are reported in the literature. Metaheuristics seem to be a powerful tool for computing good and robust solutions. However, the efficiency of algorithms based on Local Search, such as Tabu Search, suffers from the complexity of evaluating the objective function after each move. In this paper, we propose a Tabu Search algorithm which exploits simulation approach to solve chance-constrained programs. We prove its efficiency reporting the results of extensive computational experiments.
|Titolo:||A Tabu Search algorithm for solving chance-constrained programs|
|Autori interni:||ARINGHIERI, ROBERTO (Primo)|
|Data di pubblicazione:||mar-2005|
|Parole Chiave:||Algorithms; Experimentation; Performance; Stochastic Problem; Simulation; Tabu Search|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Citazione:||A Tabu Search algorithm for solving chance-constrained programs / R. Aringhieri. - Crema (CR) : Università degli Studi di Milano, Polo Didattico e di Ricerca di Crema, 2005 Mar.|
|Appare nelle tipologie:||08 - Relazione interna o rapporto di ricerca|