in this study, a hybrid algorithm is presented to tackle multi-variables robust design problem. the proposed algorithm comprises neural networks (nns) and co-evolution genetic algorithm (cga) in which neural networks are as a function approximation tool used to estimate a map between process variables. furthermore, in order to make a robust optimization of response variables, co-evolution algor...

multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...

the dynamic facility layout problem (dflp) is the problem of finding positions of departments onthe plant floor for multiple periods (material flows between departments change during the planning horizon)such that departments do not overlap, and the sum of the material handling and rearrangement costs isminimized. in this paper a new optimization algorithm inspired from colonizing weeds, invasi...

assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. in this study, we solve quadratic assignment problem (qap), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. it should be noted that any facility must be assign to only one location. in this paper, first o...

in this paper a scheduling problem in a 2-stage supply chain is discussed. suppliers are in the first stage and in the second stage, there are vehicles which carry orders to a manufacturing center. the purpose is to allocate orders to suppliers, sequence the suppliers’ production, allocate orders to transport vehicles and prioritize orders that should be carried by vehicles to minimize the tota...

e-learning model is examined of three major dimensions. and each dimension has a range of indicators that is effective in optimization and modeling, in many optimization problems in the modeling, target function or constraints may change over time that as a result optimization of these problems can also be changed. if any of these undetermined events be considered in the optimization process, t...