Journal of Advances in Industrial Engineering
Volume:46 Issue: 2, 2013

High congestion of returned product at remanufacturing facility causes substantial delays and consequently remarketing value losses for time-sensitive and high-tech products with short life cycles, such as electronic equipments. At the remanufacturing site the returned product are inspected and classified according to their quality and processing time in one of the two classes: Class 1 being admitted to the remanufacturing process and class 2 jobs that are rejected. In this paper, we provide a two-echelon supply chain; including inventory system and remanufacturing system. We propose an analytical queuing model for the decisions of the acceptance of return products and the maximum capacity of inventory system. The supply chain is modeled as queuing system and analyzed with matrix geometric method. The maximum capacity of inventory system (S) and admission decision value (k) calculated as the total expected discounted profit are maximized.

A Basic assumption of MADM methods such as SAW and TOPSIS is the statistical independence of criteria. Violating this assumption would result in erroneous decisions. However, there are many cases in which criteria are dependent and based on this situation decision has to be made. In this paper, an approach based on the property of principal component analysis (PCA) in producing independent variables is developed. In addition, weights of criteria are considered for decision making considering the fact that PCA does not take them into account. Since each of the new components obtained from PCA is a linear combination of the initial criteria therefore one cannot say whether the new component is a larger the better variable or a smaller the better one so the decision making is difficult. To determine the direction of the new components, we developed a new method based on the variation mode chart. This method uses the weights of the initial criteria as well as their coefficients in the new components and considering the direction of the initial criteria it determines the direction of the new components. After that it becomes obvious which component is a larger the better or a smaller the better variable. Meanwhile, the basic assumption of criteria independency is met. To show the efficiency of the proposed method, a real case in a military decision making problem as well as a numerical example is presented. In the military decision making problem, the Mann-Whitney non parametric test shows that the ranking of alternatives obtained from proposed method has more accordance with the ranking derived from expert's choice in comparison with the other methods ignoring the effect of dependencies. For more assurance about the performance of the proposed method, an example with a large number of alternatives and attributes (20 alternatives and 10 criteria) is presented. Using the properties of PCA, the initial criteria are replaced by four independent components. After determining the direction of new components using TOPSIS and SAW two different rankings are produced to choose from. For the validation of the proposed method this problem was also solved by ignoring dependencies of alternatives. The final results showed that using the proposed method will result in similar ranking under implementation of different MADM methods, herein Topsis and SAW. Ignoring the dependency would cause very different and sometimes conflicting ranking under implementation of different MADM techniques. In other words, the proposed method results in more robust ranking compared to the methods that ignore the dependency of criteria.

This paper proposes a new mathematical model for the integrated procurement-production-distribution problem of a fuzzy mixed integer linear programming (FMILP) type. Considering the uncertainty in real problems, a number of parameters such as demand, capacity, and cost where their values are not available or known precisely, have been considered as trapezoidal fuzzy numbers. To solve fuzzy mixed-integer linear programming model it is first converted into a crisp model using two ranking of fuzzy numbers, and then the crisp model is solved. To validate the proposed model, examples with different size are generated by random data and then solved by both crisp and fuzzy models. By comparing the related results, it is shown that fuzzy model has a smaller value for the objective function than for the crisp model and the fuzzy model does not increase the number of computations and run time significantly.

The environmental rules of reverse logistic networks have caused important economic growth in the past decades. To integrate forward logistic networks with reverse logistics networks a helpful method is to design both networks simultaneously. Considering more retrieval choices in modeling reverse logistic systems can be very critical. This article contains a mixed integer linear programming model which can be used to design a forward/reverse multi-product, multi- echelon, simple period with limited capacity, under uncertainty situation network. The desired network encompasses the retrieval and remanufacturing choices. The final purpose of this article is to minimize the whole cost of the network.

In design of experiments, analysis and identifying those variables that affect the outputs are of interest. Response surface methodology is a mathematical-statistical method to optimize the experiment outputs. This method tries to find the best response levels by optimizing the design variables called factors. In many engineering applications, robust design has become the most important issues. Robust design is that can be more and more reliable against possible stresses Considering some outputs related to reliability aspects, response surface methodology can lead towards the mentioned purposes. Since there are few researches related to this topic in the literature, optimization of multiple response surfaces related to reliability characteristics are considered in this study.

This research presents and solves a new mathematical model for School Bus Routing Problem (SBRP). SBRP is a specific case of Vehicle Routing Problem (VRP). Despite prevalent models, this model includes location and routing simultaneously. Besides, the vehicles are non-homogenous. In addition, instead of locating schools which are the depots, we consider locating bus stops that are mentioned 'customer's in the simple Location Routing Problem (LRP). This problem itself has led to a change in sub-tour elimination constraint. In contrast to the other articles we solve location and routing simultaneously. In one of these models, students related to different schools can receive service by same station and in other models each school have specific stations. To solve this model, we proposed a meta-heuristic Scatter Search (SS) algorithm. Afterward, we coded the model by GAMS software. Finally the results derived from SS algorithm are compared with results derived from GAMS. Consequently we figured out that SS algorithm produces results in more reasonable time with acceptable errors.

This paper deals with the product mix problem using the concept of Theory Of Constraints (TOC). Theory of constraints is one of the most efficient approaches which have been applied to solve the product mix problem heuristically. Although there are numerous heuristic and meta-heuristics to solve this problem, finding the optimal solution in a reasonable time is still a challenging issue. In this paper, a novel procedure inspired by multi-agent decision making concepts, is developed to generate better initial solutions upon which the existing TOC-based product mix algorithms can reach solutions with better quality. The superiority of the proposed procedure is validated by two existing algorithms through a well-known problem instance in the body of literature.

In this paper a new problem of three stage disassembly-assembly scheduling is introduced and reviewed. This problem, which was arisen from the aviation industry characteristics, is a generalization of the two stage assembly scheduling problem. Products (helicopters) in the aviation industry return to assembler for annual overhaul repair services. In the first stage helicopters are disassembled into their components. After that, the components are sent to their dedicated machines in the second stage for repair operations concurrently. In the second stage, some of the components may require one or more spare parts. Repair operations of the components can be started when their required spare parts are available at that time. After completing all of the component operations, the assemble stage can be started. In this problem we consider repair scheduling of components and lot sizing and scheduling of their required spare parts with the objective of minimizing sum of total completion times of the retuned products and spare parts inventory costs. In this study, an integrated formulation approach has been employed for the problem and a linear MIP was developed. A base case from aviation industry was solved and results were analyzed. The sensitivity analysis of the problem was carried out by changing key parameters of the base case. Selecting a repair strategy or changing to a new strategy is a key decision in the aviation industry. In this study, changing to a new strategy has been compared with three existing repair strategies in 120 problem instances using three types of data sets. Results showed that various strategies could be selected depend on the quality of returned products. The repairing shared items strategy has a better performance in average compared to the other strategies.

The capacitated location-routing problem (CLRP) is a new research area in logistics and distribution management. This problem combines two difficult problems: the facility location problem (FLP) and vehicle routing problem (VRP). The goal of the CLRP is to open a subset of depots, assign the customers into open facilities, and then design vehicle tours in order to minimize the total cost. The time windows constraint has numerous real-life applications, however there are little attention to this fact in the CLRP. This paper, considers the CLRP with hard time windows (CLRPHTW). At first, a mixed integer linear programming (MILP) formulations for the CLRPHTW is presented, then a meta-heuristic approach based on variable neighborhood search for solving the CLRPHTW is proposed. In order to evaluate the performance of the suggested method, this framework is tested on a set of instances. The experimental results show the effectiveness of the proposed approach.