Journal of Advances in Industrial Engineering
Volume:49 Issue: 2, 2015

Sohrabi and Nalchigar (1389), proposed a new data envelopment analysis (DEA) model to identify the most efficient decision making unit (DMU) considering imprecise data. In this paper it will be shown that the proposed model is not able to determine the most efficient DMU and the model randomly introduced an efficient DMU as the most efficient. It will be shown also that the proposed model to determine the most efficient DMU in the case of variable return to scale have the same drawback and also may be infeasible in some cases. To overcome the drawbacks new integrated models will be presented. In addition, to find and rank other most efficient DMUs an algorithm will be proposed. By using the presented model in the paper decision maker can find the most efficient DMU by solving only one linear integer programming. Applicability of proposed model is indicated by using imprecise data set includes specifications of 18 suppliers.

This paper presents a multi-attribute decision-making model to rank and select the best zones of the city of Tehran in order to add new emergency services. The purpose of this decision-making problem is to prioritize the zones which have a higher need to emergency services, so that the emergency services to people in different zones get optimized. Criteria decision making model have been chosen on the basis of expert's opinions so that the ranking of these models, satisfactorily will improve response time to requests of emergency services. A three-level hierarchical structure is proposed and fuzzy AHP approach is used for ranking alternatives and the optimal location of the emergency services. Paired comparison matrices of decision making criteria and alternatives are built based on data sets of Traffic and Transportation Studies Organization Of Tehran and its staff, Geophysics Institute of University of Tehran and Tehran Municipality Cultural Department.

In this paper, a hybrid fuzzy rule-based system and a bi-objective linear programming model is proposed to solve the unit commitment problem in a power generation company. The mathematical model aims to minimize the total efficiency of active units and failure risk of units simultaneously whose objective function's coefficients are derived from a fuzzy rule-based system constructed by expert's subjective opinions and knowledge. A real case study is also presented to shoe the applicability of the proposed model in practice.

Amount of daily sunshine hours is one of factors that influence number of solar panel in an Off Grid Photovoltaic System. With the different months, the amount of daily sunshine hours vary and in summer amount of daily sunshine hours is more than winter. When designing a system and calculation number of system components, amount of daily sunshine is used. But in the winter due to below-average sunshine hours, loss of power and Due to above-average sunshine hours in summer, there is an extra electrical capacity.
In this paper for Kermanshah daily sunshine hours in the 12 months of the year and the average daily sunshine hours during the year, 13 plans are presented for the design of photovoltaic systems and based on reliability and cost of power system, Suitable plans is selected.
For economic evaluation life cycle cost method in 30 years due to 18% discount is used. In this paper prices and costs is based on Iranian market in 2012 and is in dollar. The results show that the June and July plans for photovoltaic systems, are less expensive and less reliable access to electricity, but December has the highest cost and highest reliability

Decentralization allows channel members to make their decisions, independently. In this decentralized channels, members may have different power to make its decisions. Hence, decisions of each members may influence on the other members’ decisions. To model such situations, bi-level programming models are useful. In this study, a supply chain including one manufacturer and multiple competitive retailers are considered. The manufacturer produces several perishable and substitutable products. The problem is formulated as a multi-follower bi-level programming model. Since bi-level models are often NP-Hard, simulated annealing algorithm is applied to solve the proposed model. The numerical results of sensitivity analysis indicate that in the larger markets, even increasing in the prices leads to increase the profit of members. Also, when the consumers are price-sensitive, the manufacturer and the retailers must decrease their prices to attract the consumers and increase their profits, consequently.

This paper aims to present a model for agile supply chain model in construction enterprises with performance evaluation of suppliers and contractors. Management and selection of suppliers and contractors plays an important role in process of constructions since contractors are as corner stones of construction projects. Also, contractors are the main factor in converting resources to final products. Traditionally, contractor selection in construction projects is on the basis of the lowest proposed price. However, there are various qualitative and quantitative criteria with different priorities associated in this regard. In this paper, a hybrid method of DEA/AHP/FDEMATEL is used. First, important and effective evaluation criterion are selected through FDEMATEL approach. Then, DEA/AHP method is implemented in order to evaluate and prioritize the selected indicators and to incorporate them in supply chain. Furthermore, agility is involved in the considered supply chain model. In this paper, for the first time in Iran, we have studied and designed a supply chain for civil Companies.

Many serious accidents have happened in the world where systems have been large-scale and complex, and have caused heavy damage and a social sense of instability. Furthermore, advanced nations have almost finished public infrastructure and rushed into a maintenance period. Maintenance will be more important than production, manufacture, and construction, that is, more maintenance for environmental considerations and for the protection of natural resources. From now on, the importance of maintenance will increase more and more. In the past four decades, valuable contributions to maintenance policies in reliability theory have been made.
In this thesis, maintenance activities planning problem is considered. First, maintenance activities are simulated via Awesim. Production and maintenance functions are estimated using historical data. Then simulation is carried out for different scenarios which are combinations of periodic maintenance, and outputs are computed. Since the problem is multi-criteria, data envelopment analysis (DEA) method is used to select the preferred policy.

The traditional economic production quantity (EPQ) model assumes that the production products are all perfect. It is not always true in the real production system, due to imperfect production process or other factors, imperfect quality items maybe produced. Furthermore, it is well-known that the total production-inventory costs can be reduced by reworking the imperfect quality items produced with a relatively smaller additional reworking and holding costs. In addition, the permissible delay in payments offered by the supplier is widely adopted in the practical business market. In this study, we explore the effects of the reworking imperfect quality items and trade credit on the EPQ model with imperfect production processes and complete backlogging. A mathematical model which includes the reworking and shortage costs, interest earned and interest charged is presented. Besides, an arithmetic-geometric mean inequality approach is employed and an algorithm is developed to find the optimal production policy. Furthermore, some numerical examples and sensitivity analysis are provided to demonstrate the proposed model.

Todays, improving the competitiveness of companies and rapidly respond to diverse customer demands require efficient management of the supply chain. One of the effective indices in supply chain is integration and one of the innovative approaches in this field is Vendor Managed Inventory. In this paper, an integrated model based on vendor managed inventory system for deterioration and amelioration items in a three-level supply chain is developed. To coordinate retailers and producers in the supply chain the common replenishment cycle is used that is a technique of VMI system. The assumptions of this model consist of deterministic demand rate for each retailer, certain production and deterioration rates. Furthermore, in this paper the amelioration of items is mentioned that follow the Weibull distribution. First, the mixed integer non linear mathematical model is presented. Second, to validate the proposed model, a numerical example is given. To solve the model, genetic algorithm method is presented.

This paper presents a new mathematical model for combined manpower vehicle routing, in which working teams are considered as servers. Having teams with different competency affects the service duration and cost that expands the flexibility of scheduling. A fleet of vehicles with different speed and cost of movement is used to transport these teams to visit the customers before the due date. The goal is to find an efficient schedule for the teams and vehicles movement to serve all the customers in order to minimize the total cost of serving, routing and lateness penalties. A mixed-integer programming model is presented and a number of tests problems are generated. To solve the large-sized problems, two meta-heuristics approaches, namely genetic algorithm (GA) and particle swarm optimization (PSO) are developed, and then the Taguchi experimental design method is applied to set the appropriate values of the parameters. The obtained results show the higher performance of the proposed GA compared with PSO in terms of solutions quality within comparatively shorter periods of time.

Fault tolerance is one of the important issues in industries like transportation, military, chemical and nuclear sector. Reliability and safety are the two vital attributes of fault tolerant systems, and redundancy is a common way to improve these parameters. This article studies the impact of including cold standby spares in system architecture. To do this, it uses the Markov model of the system due to its capabilities in incorporating and modeling of priorities, functional dependencies, timing relations, reconfiguration issues and events sequences, existed in the system dynamic. Previous research works in the domain of reliable and fault tolerant systems, have not presented general formulas for evaluating the reliability and safety of systems supported with cold spares. This article presents closed formulas for these attributes by which the impact of the number of spares, failure rate of modules, coverage factor, and switch quality can be studied on the system performance.

One of important issues in designing a supply chain is supplier selection. The issue is complicated because each of suppliers should met some criteria from buyer and choosing among them is actually a MCDM problem. So there is a need for a structured and systematic approach to solve this problem. In this article we address supplier selection in advertising industry and two new criteria are proposed. Also a new approach combining the techniques of MDL and fuzzy Topsis is proposed to evaluate suppliers in the industry.

Reverse logistic and recursive management is one of the important subjects in logistic and supply chain management which is not drastically considered in our country in the last two decades. A lot of companies and industries of advanced countries have begun studies in terms of reverse logistics and considered it as one of the most crucial process in their supply chain. Continues improvement and consumer satisfaction is the primary purpose of indirect logistics system. Reverse logistic network design, as one of the strategic supply chain management levels, which is very principal.
In this paper, an integrated direct and reverse logistic considering production, distribution, customer, devastation, retrieval centers under uncertainty is developed. In this model, cost parameters are not certain which the scenario-based robust optimization method is applied. The aim of the model is to minimize the total cost and obtain robust solution. Finally, a practical case study is presented to verify the proposed model. Moreover an efficient solution algorithm is presented. The computational results illustrate the efficiency of the proposed approach.