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Optimization in Industrial Engineering - Volume:10 Issue: 22, Summer and Autumn 2017

Journal of Optimization in Industrial Engineering
Volume:10 Issue: 22, Summer and Autumn 2017

  • تاریخ انتشار: 1396/03/16
  • تعداد عناوین: 10
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  • Yitagesu Yilma Goshu *, Amare Matebu, Daniel Kitaw Pages 1-13
    The purpose of this research is to present an alternative approach for measuring productivity in manufacturing companies. To achieve the research objective, an in depth investigation on the existing productivity measurement and analysis practices of a case manufacturing company has been carried out through both qualitative and quantitative approaches. The investigation result has shown that there are serious problems in measuring and analyzing of productivity at company level. Following the existing practices analysis result, a new productivity measurement and analysis framework has been developed. The developed productivity measurement and analysis framework is found to be simple to understand, detects problem easily and realistically, compatible to modern management systems and tools, and potentially adaptable to similar manufacturing companies.
    Keywords: Productivity measurement, productivity analysis, manufacturing company
  • Gezahegn Tesfaye Dadi *, Daniel Kitaw Azene Pages 15-23
    Manufacturing companies must find competitive methods to produce products cheaper, faster and better to continuously satisfy their customers and acquire organizational success. For continuous improvement to be more successful, hybrid programs such as integrated TQM and JIT approaches give better results. As the existing TQM and JIT integrated approaches in literatures are not analogous, this study provides a consolidated result. Moreover, the study identifies two additional practices that the TQM and JIT integrated frameworks must contain to continually improve organizational successes. The two practices are the necessity of interaction between the core company and the external stakeholders (such as governmental organizations, universities, banks, research institutions and others) and the need of technological capability accumulation process, which were either neglected or only limitedly discussed in the existing literatures of TQM and JIT philosophies. Thus, this study reviews the existing practices of TQM and JIT programs, explores their relationships, provides modifications to the integrated TQM and JIT framework by developing an improved integrated TQM and JIT approach that can enhance the continuous improvement efforts and global successes of companies. The study also provides a case application for Ethiopian leather and leather manufacturing companies to practically apply the model proposed in this research and to solve the related problems of the companies.
    Keywords: organizational success, continuous improvement, TQM, JIT, Innovative Framework
  • Jitendra Kumar, Nirjhar Roy, Ali Mostafaeipour *, Mojtaba Qolipour Pages 25-38
    Supply chain management (SCM) addresses the management of materials and information across the entire chain from suppliers to producers, distributors, retailers, and customer. The theory of supply chain management suggests that lead time reduction is a pioneer to the use of market mediation to reduce transaction uncertainty in the chain, which can be conceptualized as the primary goal of supply chain management. In the past few decades, scholars gave ample attention about the impact of inventory on SCM. This paper relates to the development of a lot sizing model for a single component multiple delivery system with variable demand and lead time of a multinational transformer company. Two models and the modification were developed on the basis of the following assumptions. For first model distribution of demand is normal, distribution of procurement lead time is exponential and the quantity is coming in a single lot. For second model distribution of demand is normal distribution of ‘procurement’ and ‘administrative delay’ lead time is exponential and the quantity is coming in a single lot.
    Modification of the first model has been done by taking the effect of multiple deliveries in the models and correcting the Re-order point as obtained from the previous models. The results were observed by the second model and analysis has been done for different parametric conditions. The effect of multiple deliveries is also taken into account. The optimum re-order point and economic ordering quantity with various different inputs have been discussed.
    Keywords: SCM (Supply Chain Management), Lot size, Economic Order Quality (EOQ), Lead time, ROP (Re-order point)
  • Habib Heydari, Mohammad Mahdi Paydar *, Iraj Mahdavi Pages 39-48
    Today’s business environment has forced manufacturers and plants to produce high-quality products at low cost and the shortest possible delivery time. To cope with this challenge, manufacturing organizations need to optimize the manufacturing and other functions that are in logical association with each other. Therefore, manufacturing system design and supplier selection process are linked together as two major and interrelated decisions involved in viability of production firm. As a matter of fact, production and purchasing functions interact in the form of an organization’s overall operation and jointly determine corporate success. In this research, we tried to show the relationship between designing cellular manufacturing system (CMS) and supplier selection process by providing product quality considerations as well as the imprecise nature of some input parameters including parts demands and defects rates. A unified fuzzy mixed integer linear programming model is developed to make the interrelated cell formation and supplier selection decisions simultaneously and to obtain the advantages of this integrated approach with product quality and consequently reduction of total cost. Computational results also display the efficiency of proposed mathematical model for simultaneous consideration of cellular manufacturing design and supplier selection as compared to when these two decisions separately taken into account.
    Keywords: Cellular manufacturing, supplier selection, product quality
  • Farshad Faezy Razi *, Naeimeh Shadloo Pages 49-59
    Considering the concept of clustering, the main idea of the present study is based on the fact that all stocks for choosing and ranking will not be necessarily in one cluster. Taking the mentioned point into account, this study aims at offering a new methodology for making decisions concerning the formation of a portfolio of stocks in the stock market. To meet this end, Multiple-Criteria Decision-Making, Data Mining, and Multi-objective Optimization were employed. First, candidate stocks were clustered using two-step clustering method. Available stocks in each cluster were independently ranked using grey relational analysis. Firefly algorithm was employed for Pareto analysis of risk and ranking. The results of clustering in the stocks revealed that all candidate stocks were not placed in one cluster. The results of robustness analysis employed in ranking method verified the accuracy of calculations in the grey relational analysis through stock repetition of candidates in each cluster.
    Keywords: Firefly Algorithm, Grey Relational Analysis, Multiple-Criteria Decision-Making, Portfolio Optimization, Two-Step Clustering
  • Abolfazl Kazemi *, Ali Shakourloo, Alireza Alinezhad Pages 61-71
    This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is proposed and then the proposed model is solved as a fuzzy goal programming model to fulfill aspiration level of each objective. Furthermore, numerical example of efficient portfolio selection is provided to illustrate that proposed model is versatile enough to be applicable to various unexpected conditions.
    This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is proposed and then the proposed model is solved as a fuzzy goal programming model to fulfill aspiration level of each objective. Furthermore, numerical example of efficient portfolio selection is provided to illustrate that proposed model is versatile enough to be applicable to various unexpected conditions.
    Keywords: Multi-objective portfolio selection, Theory of possibility, Fuzzy goal programming model
  • Vahid Mohagheghi, Seyed Meysam Mousavi, Behnam Vahdani * Pages 73-80
    Effective project management requires reliable knowledge of cash required in different stages of project life cycle. Getting this knowledge is highly dependent on sophisticated consideration of project environment. Nature of projects and their environments are associated with uncertain conditions. In this paper, a new project cash flow assessment method based on project scheduling is proposed to foresee project's cash flow in their different stages. Interval-valued fuzzy sets (IVFSs) are applied to address the uncertainty of activity durations and costs. First, an IVF-project scheduling method is proposed to calculate early start time and early finish time of activities under IVF-environment and based on that, a new method of cash flow assessment is introduced under IVF-environment. For the purpose of illustration, the proposed method is implemented to generate cash flow of main activities of a large-scale project. The results show the flexibility of presented assessment method in expressing uncertainty, in addition to its capability in risk evaluation. Furthermore, using alpha-cuts to address different levels of uncertainty and risk provides a comprehensive insight of the cash required in different stages of project life cycle under different levels of risk and uncertainty. Finally, the results are discussed and the proposed method is believed to be useful in the project evaluation.
    Keywords: Cost forecasting, Project cash flow, Fuzzy project scheduling, Assessment method, Interval-valued fuzzy sets (IVFSs)
  • Elham Jelodari Mamaghani *, Mostafa Setak Pages 81-91
    The location-routing problem is the most significant and yet new research field in location problems that considers simultaneously vehicle routing problem features with original one for achieving high-quality integrated distribution systems in beside of the global optimum. Simultaneous pickup and delivery based on time windows are the two main characteristics of logistic management that have been used separately in most of the location routing problem in spite of their various real-life application with together. Furthermore, distribution manager always trying to create a distributed system layout along with the lowest total system cost and enhancing service levels for providing all customers satisfaction. Accordingly, in the current paper is considered the mentioned gap, that is to say the bi-objective capacitated location-routing problem based on simultaneous pickup and delivery with soft time window and multi depots (BOCLRPSPDSTW). For achieving the main goal, bi-objective mixed-integer linear programming model for BOCLRPSPDSTW, on the one hand minimizing summation of all problem costs and on the other hand, for meeting customer service level minimizing maximum summation of delivery times and service times are addressed. To solve the presented model, NSGAII and NRGA are proposed and at last efficiency of the anticipated solutions are depicted by testing them in a data set.
    Keywords: Location-routing problem with time window, Location-routing problem, Simultaneous pickup, delivery, Mixed integer linear programming, bi-objective location-routing problem
  • Naser Azim Mohseni, Ahmad Fakharian* Pages 93-101
    This paper describes a low computational direct approach for optimal motion planning and obstacle avoidance of Omni-directional mobile robots within velocity and acceleration constraints on the robot motion. The main purpose of this problem is the minimization of a quadratic cost function while limitation on velocity and acceleration of robot is considered and collision with any obstacle in the robot workspace is avoided. This problem can be formulated as a constraint nonlinear optimal control problem. To solve this problem, a direct method is utilized which employs polynomials functions for parameterization of trajectories. By this transforming, the main optimal control problem can be rewritten as a nonlinear programming problem (NLP) with lower complexity. To solve the resulted NLP and obtain optimal trajectories, a new approach with very small run time is used. Finally, the performance and effectiveness of the proposed method are tested in simulations and some performance indexes are computed for better assessment. Furthermore, a comparison between proposed method and another direct method is done to verify the low computational cost and better performance of the proposed method.
    Keywords: Direct trajectory planning, Obstacle avoidance, Motion constraints, Omni-directional mobile robots
  • Hamed Soleimani *, Mostafa Zohal Pages 103-114
    Forward-reverse logistics network has remained a subject of intensive research over the past few years. It is of significant importance to be issued in a supply chain because it affects responsiveness of supply chains. In real world, problems are needed to be formulated. These problems usually involve objectives such as cost, quality, and customer's responsiveness and so on. To this reason, we have studied a single-objective model for an integrated forward/reverse logistics network design. This model includes seven echelons; four echelons in the forward direction and three in the reverse direction. We present an effective algorithm based on ant colony optimization for this NP-hard problems to maximize the benefit. The proposed metaheuristic algorithm is a new approach in the field of closed-loop supply chain network design. Furthermore, the developed model is a three-objective one which regards incomes, costs, and the emissions of CO2. A new approach is utilized in order to integrate three various-dimension objective functions. The performance of the proposed algorithm has been compared utilizing the optimum solutions of the LINGO software. Besides, various instances with small, medium, and large sizes are generated and solved so as to make the evaluation of the algorithm reliable. The obtaining results clearly demonstrate superiority performance of the proposed algorithm.
    Keywords: Logistics network, Forward-reverse supply chain, single-objective, ant colony optimization