Simulated annealing algorithm for facility layout problem with fixed machines and multiple process routes

[ENG] A good placement of facilities contributes to the overall efficiency of operations and may reduce the total operating expenses up to 50%. Due to the variety of considerations found in the articles, researchers do not agree about a common and exact definition of layout problems. In a general perspective, the researches on facilities location problem available in the literature are classified in two categories. In the first category it is assumed that the locations are known in advance and the problem is to assign facilities to different locations. In second category it is assumed that locations are not known preferment and must be determined in a continuous area. The problem studied in this paper refers to the first category

Two-echelon Supply Chain Considering Multiple Retailers with Price and Promotional Effort Sensitive Non-linear Demand

This study deals with the effects of a supply chain (SC) with single product, multiple retailers and a manufacturer, where the manufacturer(he) produces lotsize of the product that contains a random portion of imperfect quality item. The imperfect quality products are sold in a secondary shop. The new contribution of this paper is a new non-linear demand function. Demand of the end customers varies with pricing and promotional effort of the rivalry amongst the retailers which can be used for the electronic goods, new lunched products, etc. We investigate the behavior of the supply chain under Manufacturer-Stackelberg(MS), and Retailer-Stackelberg(RS) model structures. The nature of the mentioned models provides great insights to a firm’s manager for achieving optimal strategy in a competitive marketing system. Within the framework of any bilevel decision problem, a leader's decision is influenced by the reaction of his followers. In MS model structure, following the method of replacing the lower level problem with its Kuhn-Tucker optimality condition, we transform the nonlinear bilevel programming problem into a nonlinear programming problem with the complementary slackness constraint condition. The objective of this paper is to determine the optimal selling price and promotional effort of each retailer, while the optimal wholesale price of the perfect quality products are determined by the manufacturer so that the above strategies are maximized. Finally, numerical examples with sensitivity analysis of the key parameters are illustrated to investigate the proposed model

A probabilistic multi objective CLSC model with Genetic algorithm-ε_Constraint approach

In this paper an uncertain multi objective closed-loop supply chain is developed. The first objective function is maximizing the total profit. The second objective function is minimizing the use of row materials. In the other word, the second objective function is maximizing the amount of remanufacturing and recycling. Genetic algorithm is used for optimization and for finding the pareto optimal line, Epsilon-constraint method is used. Finally a numerical example is solved with proposed approach and performance of the model is evaluated in different sizes. The results show that this approach is effective and useful for managerial decisions

Multi-objective optimization of integrated lot-sizing and scheduling problem in flexible job shops

This paper investigates a particular integrated lotsizing and scheduling problem in a multi-level multi-product, multi-machine and flexible routes environment that is called flexible job shop problem (FJSP). The considered problem involves making simultaneous decision in sequencing operations, sizing lots and assigning machines to operations in order to optimize a multi-objective function including minimizing sum of the system costs, total machines workload and makespan, while a given demand is fulfilled without backlogging. Due to the complexity of the problem, a hybrid meta-heuristic based on a combination of Genetic algorithm and particle swarm optimization algorithm is developed to solve it. Additionally, the Taguchi method is employed to calibrate the influential parameters of the meta-heuristic and boost its capabilities. Finally, the performance of the proposed algorithm is compared with some well-known multi-objective algorithms such as NSGAII, SPEA2 and VEGA. Regarding to the computational results, the hybrid algorithm surpasses the other algorithms in the closeness of solutions to pareto optimal front and diversity criteria