in this paper the conditional location problem is discussed. conditional location problems have a wide range of applications in location science. a new meta-heuristic algorithm for solving conditional p-median problems is proposed and results are compared to those of the previous studies. this algorithm produces much better results than the previous formulations.

this paper investigates the problem of selecting and scheduling a set of projects among available projects. each project consists of several tasks and to perform each one some resource is required. the objective is to maximize total benefit. the paper constructs a mathematical formulation in form of mixed integer linear programming model. three effective metaheuristics in form of the imperialis...

In this research, an integrated inventory problem is formulated for a single-vendor multiple-retailer supply chain that works according to the vendor managed inventory policy. The model is derived based on the economic order quantity in which shortages with penalty costs at the retailers` level is permitted. As predicting customer demand is the most important problem in inventory systems and th...

This paper presents a new optimization algorithm to design an optimal proportional, integral, derivative (PID) controller in hydro-turbine generator governor for damping output frequency oscillations. In this research, we utilize a stochastic and optimal based PID controller to control frequency-response of the hydro turbine. The proposed algorithm is employed to design an optimal PID controlle...

Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate pro...

microarray data have an important role in identification and classification of the cancer tissues. having a few samples of microarrays in cancer researches is always one of the most concerns which lead to some problems in designing the classifiers. for this matter, preprocessing gene selection techniques should be utilized before classification to remove the noninformative genes from the microa...

nowadays, software cost estimation (sce) with machine learning techniques are more performance than other traditional techniques which were based on algorithmic techniques. in this paper, we present a new hybrid model of multi-layer perceptron (mlp) artificial neural network (ann) and ant colony optimization (aco) algorithm for high accuracy in sce called multilayer perceptron ant colony optimi...