JOURNAL OF INDUSTRIAL ENGINEERING RESEARCH IN PRODUCTION SYSTEMS (IERPS)
Year:2019 | Volume:6 | Issue:13 |Papers Count:7

In today’ s world, changes in the economy and industry field occur in higher speed compard to the past time. The main aim of organizations and companies is to preserve and increas the benefit as well as survive in the commerical fields. This matter has caused in large scale because of that companies the globalization economical activity along with the rapid Increasement of the technical and restricted sources to compete closely together. For the companies, the competitive benefits for example as to become efficient related to the affairs such as supply chain. Additionally, because of governmental rules, green affairs and development the social responsibility concept, management the closed loop supply chain field has attained many researches interests. Closed loop Supply chain involve forward and reverse both together and the main aim of it’ s designing is to mix up the environmental observations with the traditional supply chain using accmulating the used products and operations related to the them as well. In this paper a multi objective multi period multi producst closed loop supply chain mathematical model considering green matters and compensative shortage as well as discounts has been developed. Firstly, closed loop supply chain mathematical model has been solve using three multi objective decision maker methods and numerical results have been reported in large scale. Secondly, regarding to the uncertainty of same of the parameters, the robust optimization model related to the main model has been formed and solved using multi objective decision maker methods.

In this paper, the problem of scheduling the job shop production is considered, which, while being applicable as one of the complex issues in the field of combinatorial optimization, has been raised and this has caused the researchers to pay more attention to this problem. In this problem, given the existence of a number of workshops, the number of jobs should be processed in the workshop with a known production path that is already known. In order to solve this problem, in this paper, the problem of production scheduling is firstly modeled as a mixed integer programming. Then, due to the limitations of the exact solving using this model, the surface cutting method is proposed to create inequalities this is valid for the problem in the framework of branching and cutting algorithm. The aim of adding this set of inequalities is to create a lower bound, which, while the feasible solutions are not eliminated by them, accelerates the solution in the framework of branch & cut algorithm. To solve the problem optimally, the results show that the lower bound created by the re-formulated model is stronger than the lower bound created by the original relaxed model.

Integration of supply chain decisions has become one of the most attractive and practical topics for researchers. The scheduling of the production and distribution of customer orders are two most important activities of these decisions, which both of them affect the supply chain performance in timely delivery of orders and reduce costs. This study addresses the problem of integrating these two decisions. The problem has been investigated from a multi-agent point of view. A mixed integer programming model is proposed to the problem. Regarding the problem structure, first, the problem is decomposed into two problems, and then a cutting plane approach is used to solve it. The computational results indicate the proper performance of the proposed algorithm.

Supplier Selection plays an important role in supply chain management. Attention to sustainability in supply chain makes supplier selection more controversial. Current studies have concentrated on economic factors for selection and evaluation of suppliers and there are few emphasis on triple factors including economic, environmental and social elements as the sustainability factors. Also, the methods that are used for supplier evaluation is almost based on linear programming, multi-objective programming, goal programming, integer programming, and the other exact methods. But in real situation, the evaluation criteria are ambiguous, qualitative and verbal. So, in this study, a new technique based on Grey theory is proposed for supplier evaluation that can be used in ambiguous situations. This technique helps managers to decide on supplier selection problems in real scenarios. In this study, the economic, environmental and social indices for suppliers' evaluation are identified based on experts' opinion and by applying Grey theory a technique is developed for suppliers' evaluation. The novelty of this research is to develop a new technique with more levels of analysis in ambiguity, considering sustainability factors. The case study of this research is steel industry.

Different variables effect on customer decision in product selection. The most important factor are price and service provided by the manufacturer to the customer. Advertising is one of the effective factors in the selection and purchase of goods is usually done by the manufacturer to increase goodwill of manufacturer brand. Therefore in this research we use centralized game approach to find optimal price, service level & advertising level in a dual channel supply chain simultaneously. Chain used in this study included a manufacturer and a retailer in which the manufacturer sells its products through retailer and through direct channel. Demand function used in this paper provide review possibility of three elements of price, service and advertising on customer demand seamlessly at the same time. Conduct examined in this paper, is cooperative behavior. Therefore, after modeling the problem is solved by centralized approach. After numerical examples, sensitivity analysis performed in this study provide the effect of important parameters on decisions players particularly price sensitivity factor. The issue examined in this study had a variety of practical applications for example can be cited its use in airlines, manufacturing sets and retailers to determine prices, service and advertising.

Today, implementation of projects is necessary for organizations' mobility, dynamism and development as well as guaranteeing their survival. Since environment is constantly changing, the growth of quality concepts has also been taken into consideration due to the demands of customers and increasing complexity of industrial projects at the same time. This paper focuses on analyzing the key attributes of quality in gas transmission pipeline projects using gas structural equation modeling enabling a method to improve construction quality of this type of projects. In this regard, attributes (constructs) of quality extracted from research were classified into 6 elements of the highest quality project, least quality project, high quality project, low quality project, medium quality project, ideal quality project using LISREL statistical analysis tool and then the adaptability of the whole conceptual model was fitted. According to the interpretation of the results from structural equation modeling and factor loading, the representatives of the 6 classes including attributes of requirement consideration, integration, flexibility, specialism, continuity, normally(consumption energy), foresight, good documentation, technology oriented, conformance to standards, effective supervision and nice were selected. It is clear that considering these attributes is essential to achieve the desired quality in project implementation. Although, regarding all constructs can lead to success of the project.

Many companies are unable or unwilling to perform all activities of reverse logistics. Therefore, these companies assign all or some of these activities to resources (suppliers) from outside of the company. Hence, proper selection of suppliers in reverse logistics can reduce or even eliminate large amount of future problems in this area. The best supplier in reverse logistics is selected by a group of decision makers through evaluating some of conflicting criteria. These criteria are linguistic variables and they need to be quantified by giving weight to them in fuzzy environment. This research is to develop an integrated method for selecting suppliers in a way that reverse logistics requirements are also included. In this study, after identification of criteria we use the fuzzy DEMATEL approach to measure the relationships between the criteria and then, we determine the parameters associated with each option in each criterion to use them in a fuzzy group TOPSIS method in order to prioritize items by similarity to ideal solution. And finally, the best supplier will be chosen from a set of potential suppliers. A case study is given to show the influence of the proposed method.