International Journal of Industrial Engineering & Production Research

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An interactive heuristic approach can offer a practical solution to the problem of linear integer programming (LIP) by combining an optimization technique with the Decision Maker’s (DM) judgment and technical supervision. This is made possible using the concept of bicriterion linear programming (BLP) problem in an integer environment. This model proposes two bicriterion linear programs for identifying a feasible solution point when an initial infeasible solution point is provided by the decision maker or when the searching process leaves the region of feasibility seeking for a better pattern to improve the objective function. Instructions regarding the structure of such BLP problems are broadly discussed. This added property offers a great degree of flexibility to the decision making problem solving process.

The heuristic engine is comprised of four algorithms: Improve, Feasible, Leave, and Backtrack. In each iteration, when a selected algorithm has been terminated, the DM is presented with the results and asked to reevaluate the solution process by choosing an appropriate algorithm to follow. It is shown that the method converges to the optimal solution for most of the time. A solution technique for solving such a problem is introduced with sufficient details.

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Abstract The purpose of this article is to present a system dynamics (SD) model for studying the ‎interconnections among human being weight, eating habit, exercise, body fat, take-in medication, drugs-uses, and the health problems in general. Due to the fact that all of these factors have direct and indirect impacts on the expenses that insurance company have to pay this author is proposing a systems thinking approach for determining the interconnections among the factors and uses the concept of system dynamics to simulate and determine the behavior of the system. To do so, this author has reviewed key point ‎about the system thinking, related theories, and system dynamics. Next, models in ‎the form of causal loops presenting the interconnections between weight factor ‎and health problems are developed and discussed. Thereafter, a flow diagram of ‎model is constructed and the overall expenses are studied. Expense rates are classified as: operational expenses (OE), treatment expenses (TE), Medication expenses (ME), Hospitality expenses (HE), and Drug treatment expenses (DE). This article makes a significant contribution to the health ‎study issues due to the fact that it shows how a factor such as weight can have ‎impacts on hearth attack, blood pressure, and blood sugar, to mention a few, and how relate all these to the overall expenses that an insurance company have to pay at last. ‎Since, to the best of this author's knowledge, this is the first study that relates ‎weight to health problem using systems thinking concepts and system dynamics approach ‎it makes significant contribution to health literature.‎

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Abstract In the dynamic and competitive market, managers seek to find effective strategies for new products development. Since There has not been a thorough research in this field, this study is based on a review on the risks exist in the NPD process and an analysis of risks through FMEA approach to prioritize the existent risks and a modeling behavior of the NPD process and main risks using system dynamics. First, we present new product development concepts and definition. We then based our study on a literature review on the NPD risks and then provide an FMEA approach to define risks priority. Using the obtained main risks, we model the NPD process risks applying system dynamics to analyze the system and the risks effect on. A safety clothing manufacturer is considered as a case study.

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Abstract Purpose of this paper: The objectives of this paper are two folds: (1) utilizing hierarchical fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach to evaluate the most suitable RFID-based systems decision, and (2) to highlight key risks and benefits of radio frequency identification technology in healthcare industry. Design/methodology/approach: Researcher explains the importance of selection criteria for evaluation of RFID-based system. It provides key elements on radio frequency identification, fuzzy hierarchical TOPSIS methodology and an algorithm that can be followed to solve the problem. A sample problem using the algorithm is solved and results are explained. Findings: The hierarchical TOPSIS model used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. The use of the hierarchical fuzzy TOPSIS methodology offers a number of benefits: (1) it is a systematic model and straight forward to work on (2) capable to capture the human's appraisal of ambiguity when management should deal with a complex multiple objective situations. The hierarchical fuzzy TOPSIS is in some way superior to the other Fuzzy multi criterion decision making techniques, such as fuzzy analytic hierarchy process (FAHP) and classical fuzzy TOPSIS methods. This is because while in the hierarchical structure no pair-wise comparisons among criteria, sub-criteria, and alternatives are necessary to be made, it is already being taken into consideration by the model. Hierarchical fuzzy. Practical implications (if applicable): What is original/value of paper: Due to the fact that a better management of health care system is related to the full understanding of the technologies implemented and the system under consideration, sufficient background on the radio frequency identification technology is provided and the RFID systems most likely management would face with and select one are provided for decisions to be made on them. Key Words: RFID Technology, RFID-based system selection, healthcare applications, hierarchical fuzzy TOPSIS.

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Stochastic Approach to Vehicle Routing Problem: Development and Theories Abstract In this article, a chance constrained (CCP) formulation of the Vehicle Routing Problem (VRP) is proposed. The reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. Knowing that reliable computer software for large scaled complex nonlinear programming problem with 0-1 type decision variables for stochastic vehicle routing problem (SVRP) is not easily available merely then the value of an approximation technique becomes imperative. In this article, theorems which build a foundation for moving toward the development of an approximate methodology for solving SVRP are stated and proved. Key Words: Vehicle Routing Problem, Chance Constrained Programming, Linear approximation, Optimization.

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Job Satisfaction (JS) plays important role as a competitive advantage in organizations especially in helth industry. Recruitment and retention of human resources are persistent problems associated with this field. Most of the researchs have focused on the job satisfaction factors and few of researches have noticed about its effects on productivity. However, little researchs have focused on the factors and effects of job satisfaction simultanosly by system dynamics approaches.In this paper, firstly, analyses the literature relating to system dynamics and job satisfaction in services specially at a hospital clinic and reports the related factors of employee job satisfaction and its effects on productivity. The conflicts and similarities of the researches are discussed and argued. Then a novel procedure for job satisfaction evaluation using (Artificial Neural Networks)ANNs and system dynamics is presented. The proposed procedure is implemented for a large hospital in Iran. The most influencial factors on job satisfaction are chosen by using ANN and three differents dynamics scenarios are built based on ANN's result. . The modelling effort has focused on evaluating the job satisfaction level in terms of key factors which obtain from ANN result such as Pay, Work and Co-Workers at all three scenarios. The study concludes with the analysis of the obtained results. The results show that this model is significantly usfule for job satisfaction evaluation Keywords: Job Satisfaction, system dynamics, Artificial Neural Network (ANN), healthcar field.

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Abstract Purpose of this paper: The purpose of this article is to review some of the most prominent applications of RFID in industries and to provide a comprehensive review of the work done from 1985 through 2007 and the research trend on that. The effectiveness of RFID and the challenges that it is facing with are also discussed. Some applications of radio frequency identification in supply chain are briefly reviewed and three large cases of radio frequency identification implementation in supply chain are discussed. Design/methodology/approach: Provides some background on radio frequency identification, and a deep look at the researches conducted from 1985 through 2007. Articles are classified by the year of publications and each case is discussed very briefly. To obtain a good understanding of the level of the researches completed up to the end of 2007 a table and graph are used to demonstrate the summary of results. Findings: In this research, author came up with 401 articles on RFID as all are listed in a table. The findings point to this fact that research on RFID has started to pick up on year 2002 with 16 publications and then reached to its pick at year 2005 with 112 publications, and then trend went down to 42 and then up to 51 publications for years 2006 and 2007, respectively. Practical implications (if applicable): What is original/value of paper: Due to the fact that a better management of a system is related to the full understanding of the technologies implemented, sufficient background on the radio frequency identification technology is provided and the types of researches conducted so far on this matter are briefly discussed.

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Abstract It is the purpose of this article to introduce a linear approximation technique for solving a fractional chance constrained programming (CC) problem. For this purpose, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. A sample problem is presented for clarification purposes.

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Abstract: In order to evaluate the relationship between Organizational Strategies and Organizational results, a comprehensive model is required, which should be able to capture all aspects of business excellence. The EFQM model is suitable tool to observe these factors. The EFQM model consists of two main domains: Enablers and Results. The first domain which includes processes and systems in general, "enable" the organization to have higher performance or "results". On the other hand, the feedback from the results makes the organization to correct the system. Hence, a dynamic model could be appropriate in analyzing the interrelated behavior of the two main domains as well as those within the criteria and sub-criteria. This research is an effort to find the relationship between Strategies and results through system dynamics tool based upon EFQM model. In other words, this research exploits system dynamics in order to measure the effects of Strategies on Organizational results using a dynamic model. The advantage is that by changing one parameter in the Strategies, one can find how it could affect key results especially financial outcomes. Keywords: Organizational Strategies, Organizational results, Business Excellence Model, EFQM, System Dynamics

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Abstract Purpose of this paper: This paper presents an analysis toward understanding the business value components that a health care organization can drive by adopting RFID technology into its system. This researcher proposes a framework for evaluating the business value of RFID technology. To do so, emphasis is put on delivering business value through refining business processes and expanding the business model. Author illustrates the concepts drawing on the experience of nine case studies already presented on the health care topics and service industries. Thereafter, a framework, as a set of propositions based on relevant literature, case studies from the field, and author's intuition, is formulated. The proposed propositions need to be validated through empirical evidence. To fully understand this topic some applications of radio frequency identification in health care management and other industries are briefly discussed and nine cases from health care industry are studied. Design/methodology/approach: Identifies key elements of radio frequency identification through the review of healthcare management literature and case studies. For this purpose, nine cases are reviewed from the health care industry and then key features of those cases are employed to determine four proposals for further studies. Findings: To make healthcare management systems functional and successfully operational we can use radio frequency identification solutions to reduce operating costs through decreasing the labor costs, including automation, improving tracking and tracing, and preventing the lost of materials under any circumstances. Practical implications (if applicable): What is original/value of paper: The emphasis is put on delivering business value through refining business processes and expanding the business model. A framework, as a set of propositions based on relevant literature, case studies from the field, and author's intuition is formulated and presented for further studies using true case studies.

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Abstract Nowadays supply chain management has become one of the powerful business concepts for organizations to gain a competitive advantage in global market. This is the reason that now competition between the firms has been replaced by competitiveness among the supply chains. Moreover, the popular literature dealing with supply chain is replete with discussions of leanness and agility. Agile manufacturing is adopted where demand is volatile while lean manufacturing is used in stable demands. However, in some situations it is advisable to utilize a different paradigm, called leagility, to enable a total supply chain strategy. Although, various generic hybrids have been defined to clarify means of satisfying the conflicting requirements of low cost and fast response, little research is available to provide approaches to enhance supply chain leagility. By linking Leagile Attributes and Leagile Enablers (LAs and LEs), this paper, based upon Quality Function Deployment (QFD), strives to identify viable LEs to achieve a defined set of LAs. Due to its wide applicability, AHP is deployed to prioritize LAs. Also, fuzzy logic is used to deal with linguistics judgments expressing relationships and correlations required in QFD. To illustrate the usefulness and ease of application of the approach, the approach was exemplified with the help of a case study in chemical industry.

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Abstract One of the basic assumptions in hub covering problems is considering the covering radius as an exogenous parameter which cannot be controlled by the decision maker. Practically and in many real world cases with a negligible increase in costs, to increase the covering radii, it is possible to save the costs of establishing additional hub nodes. Change in problem parameters during the planning horizon is one of the key factors causing the results of theoretical models to be impractical in real world situations. To dissolve this problem in this paper a mathematical model for dynamic single allocation hub covering problem is proposed in which the covering radius of hub nodes is one of the decision variables. Also Due to NP-Hardness of the problem and huge computational time required to solve the problem optimally an effective genetic algorithm with dynamic operators is proposed afterwards. Computational results show the satisfying performance of the proposed genetic algorithm in achieving satisfactory results in a reasonable time. Keywords: hub location problem, dynamic hub covering problem, flexible covering radius, dynamic genetic algorithm.

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Abstract Project management in construction industry, in many cases, is imperfect with respect to the integration of Occupational Health and Safety (OHS) risks. This imperfection exhibits itself as complications affecting the riskiness of industrial procedures and is illustrated usually by poor awareness of OHS within project teams. Difficulties on OHS regularly came about in the construction industry. The integration of OHS risk is not systematic in construction areas in spite of progressing laws and management systems. As project safety and risk evaluation in construction industry is an important issue, thus, the way on doing evaluation and liability of estimation is necessary. In this paper, we propose a new systematic approach based on Latin Hypercube Sampling (LHS) for integrating occupational health and safety into project risk evaluation. This approach tries to identify and evaluate reinforcement effects in a systematic approach for integrating OHS risks into project risk assessment. Furthermore, the proposed method allows evaluating and comparing OHS risks before and after the mitigation plan. A case study is used to prove the workability, credibility of the risk evaluation approach and uncomplicated integration of OHS risks at a construction project. This approach enables continual revaluation of criteria over the direction of the project or when new information is obtained. This model enables the decision makers such as project managers to integrate OHS risks toward schedule plan and compare them before and after the mitigation plan. The mentioned model is found to be useful for predicting OHS risks in construction industries and thus avoiding accidents over the path of the project.

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Using Greedy Clustering Method to Solve Capacitated Location-Routing Problem with Fuzzy Demands Abstract In this paper, the capacitated location routing problem with fuzzy demands (CLRP_FD) is considered. In CLRP_FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed the vehicles and the depots have a predefined capacity to serve the customersthat have fuzzy demands. To model the CLRP_FD, a fuzzy chance constrained program is designed, based on fuzzy credibility theory. To solve the CLRP_FD, a greedy clustering method (GCM) including the stochastic simulation is proposed. Finally, to obtain the best value of the preference index of the model and analysis its influence on the final solutions of the problem, numerical experiments are carried out. Keywords: Capacitated location routing problem, Fuzzy demand, Credibility theory, Stochastic simulation, Ant colony system.

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Abstract Firms no longer compete as autonomous entities and prefer to joinin a supply chain alliance to take advantage of highly competitive business situation. Supply chain coordination has a greatimpact on Firm’sstrategic partnering and success in competitive business environment. In this paper, we propose a system dynamics simulation model for strategic partner selection in supply chain. Our model addresses a supply chain including suppliers and retailers. It presents an approach to simulateeach supplier’s (retailers) tendency to select downstream (upstream) partner selection and the impact of their policies in the whole supply chain.