جستجوی مقالات مرتبط با کلیدواژه "nsga" در نشریات گروه "صنایع"

In the articles that have been investigated by the vendor managed inventory less attention to environmental pollution or emission of green logistics is considered. In this paper, the issue of green backorder vendor managed inventory in two-echelon supply has been considered. But innovation in green conditions of this article or reducing the amount of pollution is as a function intended purpose. In view of customer facing staff shortages in the supply chain, two-echelon warehouse and limits the number of orders is considered. The first objective is to maximize profit of vendor, which includes sales minus production and distribution costs and facing to shortage cost. The second objective function is minimizing the amount of pollution caused by the movement of goods. According to the model as a model of bi-objective, non-convex and non-linear algorithms is solved by GAMS and Epsilon-Constraint on a small scale can be used to obtain the Pareto front and compare with traditional inventory management in shortage state and for large scale non-dominated sorting genetic algorithm (NSGA-II) was used to solve the model. To adjust the algorithm parameters NSGA-II Taguchi method has been exploited in this article. The results of this research is that allowed the shortage situation, the lack of cost reduction and environmental pollution reduction, the greater the amount of shipping and orders as well as the lack of a less optimal to reduce the cost of inventory shortages.

Location and routing problems in emergencies are so important. This paper considers a location–routing problem with reliability by the means of considering the probability of failure occurrence. The problem has two objectives that minimizes the total cost and maximizes the reliability. Maximizing the reliability is expressed as minimizing the expected cost of the failure. In this problem, three kinds of failures are considered, which are: failure of centers, routes and vehicles. Since travel costs is dependent on manyzparameters and hence it is not possible to estimate exactly so they are considered as fuzzy number using linguistic variables. At first, mathematical formulation of the problem is presented, and then because the problem is the NP-hard therefore, meta-heuristics algorithms are used to solve the model. Additionally, a bi-objective discrete firefly algorithm is providedand then in order to evaluate the performance of the algorithm, several test problems are implemented and compared with the NSGA-II. The results show that the biobjective discrete firefly algorithm has a better DM measure; however, it is only suitable for small to medium-sized problems due to the MID measure and it loses its efficiency in larger sizes.

This paper proposes a novel, multi-objective integer programming model for an open-shop scheduling problem (OSSP). Three objectives are to minimize the makespan, total job tardiness and earliness, and total jobs setup cost. Due the complexity to solve such a hard problem, we develop a meta-heuristic algorithm based on multiobjective scatter search (MOSS), and a number of test problems are solved by this proposed algorithm. Finally, to prove its efficiency, the related results are compared with the results obtained by the wellknown multi-objective evolutionary algorithm, called NSGA-II. The results confirm the efficiency and the effectiveness of our proposed MOSS to provide good solutions, especially for medium and largesized problems.