Title :
Selection of the best with stochastic constraints
Author :
Kabirian, Alireza ; Olafsson, Sigurdur
Author_Institution :
Coll. of Bus. & Public Policy, Univ. of Alaska-Anchorage, Anchorage, AK, USA
Abstract :
When selecting the best design of a system among a finite set of possible designs, there may be multiple selection criterion. One formulation of such a multi-criteria problem is minimization (or maximization) of one of the criterions while constraining the others. In this paper, we assume the criteria are unobservable mean values of stochastic outputs of simulation. We propose a new heuristic iterative algorithm for finding the best in this situation and use a number of experiments to demonstrate the performance of the algorithm.
Keywords :
iterative methods; operations research; stochastic processes; heuristic iterative algorithm; multi-criteria problem; multiple selection criterion; stochastic constraints; Algorithm design and analysis; Computational modeling; Context modeling; Design engineering; Discrete event simulation; Iterative algorithms; Stochastic processes; Stochastic systems; Systems engineering and theory; Toy manufacturing industry;
Conference_Titel :
Simulation Conference (WSC), Proceedings of the 2009 Winter
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4244-5770-0
DOI :
10.1109/WSC.2009.5429658
