During the last decade, reverse logistics networks received a considerable attention due to economic importance and environmental regulations and customer awareness. Integration of leading and reverse logistics networks during logistical network design is one of the most important factors in supply chain. In this research, an Integer Linear Programming model is presented to design a multi-layer reverse-leading, multi-product, and multi-period integrated logistics network by considering multi-capacity level for facilities under uncertainty condition. This model included three objectives: maximizing profit, minimizing delay of goods delivering to customer, and minimizing returned raw material from suppliers. This research gives financial incentives to encourage customers in order to return their used product. Considering that the remaining value of used products is the main incentive of a company to buy second-handed goods, a dynamic pricing approach is determined to define purchase price for these types of products, and based on that, the percentage of returned products were collected by customers. In addition, in this study, parameters have uncertainty features and are vague; therefore, at first, they are converted into exact parameters and, then, because model is multi-objective, the fuzzy mathematical programming approach is used to convert multi-objective model into a single objective; finally, the model by version 8 of Lingo is run. In order to solve a large-sized model, a non-dominated sorting genetic algorithm II (NSGA-II) was applied. Computational results indicate the effect of the proposed purchase price on encourage customers to return the used products. پرونده مقاله

The hub location problem is employed for many real applications, including delivery, airline and telecommunication systems and so on. This work investigates on hierarchical hub network in which a three-level network is developed. The central hubs are considered at the first level, at the second level, hubs are assumed which are allocated to central hubs and the remaining nodes are at the third level. In this research, a novel multi-product multi-objective model for capacitated hierarchical hub location problem with maximal covering under fuzzy condition first is suggested. Cost, time, hub and central hub capacities are considered as fuzzy parameters, whereas manyparameters are uncertainty and indeterministic in the real world. To solve the proposed fuzzy possibilistic multi-objective model, first, the model is converted to the equivalent auxiliary crisp model by hybrid method and then is solved by two meta-heuristic algorithms such as Non-Dominated Sorting Genetic Algorithm (NSGA-II) and Non-Dominated Ranked Genetic Algorithm (NRGA) using MATLAB software The statistical results report that there is no significant difference between means of two algorithms exception CPU time criteria. In general, in order to show efficiency of two algorithms, we used Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the resultsclearly show that the efficiency of NRGA is better than NSGA-II and finally, figures are achieved by MATLAB software that analyze the conflicting between two objectives. پرونده مقاله

Due to the existing competitive environment of global economy, many companies allocate their major financial and human resources to quality improvement. Since, using measurement tool is an essential component in quality analysis and highly depends on quality of measurement systems and their results; measurement systems applications after calibration are the most efficient methods in real operations. Thus, inherent changes of measurement tools can be studied by computing capability index of measurement tools. This paper aims to develop a fuzzy model for computing capability. Fuzzy model for computing capability (Cg ،Cgk) with data in the form of fuzzy triangular and trapezoidal numbers using MATLAB is developed and then a case study applying proposed method is presented. Finally, we compare presented results with classical outcomes and prove that fuzzy environment gives more flexibility, rather than classical environment. پرونده مقاله

n the scope of center location problem, transfer point location problems (TPLP) are the ones which have been studied more recently to make models more applicable in real world. The contribution of this work is to develop a model in which demand points are weighted and have a normal distribution. As an assumption, there is no transformation directly from a demand point to the service facility location. This means that the transfer point is always engaged. The contribution of work is summarized in two models. In the first model, all the points are considered in an area while in the second one the points are considered in several areas. The problem is to find out the best location for the transfer point so that the maximum expected weighted distance to all demand points through the transfer point is minimized. A mathematical solution is employed when demand points follow normal distribution, with some points of demands being in regions. Then, this model was solved by replacing real number in a real condition. We used Maple software to solve this objective function as well as MATLAB software to solve this model numerically. پرونده مقاله