This paper provides a novel framework for solving multiobjective discrete optimization problems with an arbitrary number of objectives. Our represents these as network models, in that enumerating the Pareto frontier amounts to multicriteria shortest-path problem auxiliary network. We design techniques exploiting models order accelerate identification frontier, most notably operations simplify b...

Water cycle algorithm (WCA) is a new metaheuristic algorithm which the fundamental concepts of WCA are derived from nature and are based on the observation of water cycle process and how rivers and streams flow to sea in the real world. In this paper, the task of sizing optimization of truss structures including discrete and continues variables carried out using WCA, and the optimization result...

Discrete-event simulation based optimization is the process of finding the optimum design of a stochastic system when the performance measure(s) could only be estimated via simulation. Randomness in simulation outputs often challenges the correct selection of the optimum. We propose an algorithm that merges Ranking and Selection procedures with a large class of random search methods for continu...

We consider the use of a fixed gain version of SPSA (simultaneous perturbation stochastic approximation) for optimizing a class of discrete functions. The procedure has been modified to obtain an optimization method that is applicable to cost functions defined on a grid of points in Euclidean p-space having integer components. We discuss some related results on fixed gain SPSA and describe an a...

MSC.Nastran 2001 contains the ability to apply discrete variables in the optimization process. This was done in recognition that engineers are often required to deal with discrete variables in engineering design activities. MSC developed and implemented Design of Experiments (DOE) and Conservative Discrete Design (CDD) approaches to deal with discrete variables with limited computational cost. ...