An analysis of the dynamic behavior of Evolution Strategies applied to Trav-eling Salesman Problems is presented. For a special class of Traveling Salesman Problems a stochastic model of the optimization process is introduced. Based on this model diierent features determining the optimization process of Evolution Strategies are analyzed. In addition the stochastic model is extended to explain s...

modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. in order to obtain the maximum amount of yeast (saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. to determine substrate feeding in a fed-batch bioreactor, a simulated annealing (sa) approach was examine...

This paper experiments application of different heuristic approaches to a real facility layout problem at a furniture manufacturing company. All the models are compared using AHP, where a number of parameters of interest are employed. The experiment shows that formal layout modelling approaches can be effectively used real problems faced in industry, leading to significant improvements.

The aim of this paper is to provide a parallel strategy to be used when implementing the Simulated Annealing process by distributed memory systems. It focuses the attention on the portfolio selection problem with dynamic and integer constraints on the variables. However, this method can be extended to any dynamic optimisation problem as the optimal control. In the first part it develops the seq...

in this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. in this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. to tackle the problem efficiently and effectively, an effici...

Two well known stochastic optimization algorithms, simulated annealing and genetic algorithm are compared when using a sample to minimize an objective function which is the expectation of a random variable. Since they lead to minimum depending on the sample, a weighted version of simulated annealing is proposed in order to reduce this kind of overt bias. The algorithms are implemented on an opt...

Abstract This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in Civil Engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA) [10], the differential evolution (DE) in its original fashi...

Today’s consumer market demands that manufacturers must be competitive. This requires the efficient operation of manufacturing plants and their ability to quickly respond to changes in product mix and demand. In addition, studies show that material handling cost make up between 20 and 50 percent of the total operating cost. Therefore, this paper considers the problem of arranging and rearrangin...

The optimization of water distribution networks are complex, multi-modal and discretevariable problems that cannot be easily solved with conventional optimization algorithms. Hence, evolutionary techniques such as genetic algorithms and simulated annealing have been extensively employed during the last decade. This study adopts a Tabu search (TS), which is an evolutionary method based on explic...

In this paper, a mixed-integer linearized programming (MINLP) model is presented to design a group layout (GL) of a cellular manufacturing system (CMS) in a dynamic environment with considering production planning (PP) decisions. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. There are also some features that make the presented...