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Optimization in Industrial Engineering - Volume:10 Issue: 21, Winter and Spring 2017

Journal of Optimization in Industrial Engineering
Volume:10 Issue: 21, Winter and Spring 2017

  • تاریخ انتشار: 1395/10/26
  • تعداد عناوین: 10
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  • Hossein Barghi Jond *, Vasif V. Nabiyev, Rifat Benveniste Pages 1-6
    The trajectory planning, which is known as a movement from starting to end point by satisfying the constraints along the path is an essential part of robot motion planning. A common way to create trajectories is to deal with polynomials which have independent coefficients. This paper presents a trajectory formulation as well as a procedure to arrange the suitable trajectories for applications. Created trajectories aimed to be used for safe and smooth navigation in mobile robots. First, a trajectory problem is formulized by considering a border on the robot’s acceleration as the constraint. Also, initial and final conditions for the robot’s velocity along the straight path are settled. To investigate that suggested trajectories perform motions with continuous velocity and smooth acceleration, three trajectory problems are formulated using 3rd, 4th and 5th degree of polynomials. The high-degree polynomials are used because of providing of smoothness, but there is complexity in the calculation of additional coefficients. To reduce the complexity of finding the high-degree polynomial coefficients, the acceleration constraint is simplified and this process is based on a certain scenarios. Afterwards, the coefficients of the used polynomials are found by taking into account the acceleration constraint and velocity conditions. Additionally, to compare the obtained solutions through proposed scenarios, the polynomials` coefficients are solved numerically by Genetic Algorithm (GA). The computer simulation of motions shows that as well as acceleration constraint, the velocity conditions at the beginning and at the end of motion are fulfilled.
    Keywords: Motion Planning, Trajectory Planning, High, order Polynomials, Velocity Conditions, Acceleration Constraint, Genetic algorithm
  • Kassu Jilcha *, Daniel Kitaw, Birhanu Beshah Pages 7-17
    The purpose of this study is to develop a conceptual model of Workplace safety and Health Knowledge diffusion. As workplace safety is becoming a global issue in the competitiveness of the business environment, knowledge diffusion model to workplace safety is found a mandatory tool to create awareness of the society and conceptual model is developed. Literature review was conducted in collecting data. Different journal articles were reviewed regarding occupational safety and health and knowledge diffusion. The interview and personal experiences are also included in the methodology. Finding shows that in today’s manufacturing industries, globalization and industrialization have resulted in increasing societal economic development. With this globalization effect, workplace hazards are getting increased from time to time and imposed many challenges on society. Some of them are workplace safety hazards, high costs, loss of productivity and organizational competitiveness advantage. These challenges emanated from the absence of awareness creation. The literatures finding ratifies that the global occupational safety knowledge diffusion is found to be at its infant stage. The research implementation is conceptual model development process which is an ideal for developing economies unless the awareness to the workplace safety will be conducted in line with the model. In practice, the finding solves retiring industry-university linkage, weak top management commitments and weak awareness scenario of the employees of any organization. In order to censor these workplace safety improvement hampering situations, it discloses a clue for knowledge diffusion and forward the way how to diffuse workplace safety and health knowledge. Finally, the originality/Value shows that even though existing researches contribution to workplace safety is undeniable, many of the researches overlooked the knowledge diffusion process through phase analysis model development. Therefore, this study reveals to fill the gap found in the researches.
    Keywords: Occupational safety, knowledge diffusion, occupational health, knowledge management
  • Mohammadreza Shariari *, Nazanin Pilevari Pages 19-28
    Regarding to the diversified needs of domestic and global customers and various products of domestic and global competitors, importance of agility in supply chain management becomes more important. Suppliers have to provide materials and essential resources of manufacturers in a short time without any lead time.
    In this research, we identified many criteria for agility in sanitation supply chain. Then with utilization of Fuzzy Delphi, ideas of experts about criteria have been gathered in 8 final criteria. Next step is devoted to prioritization of five suppliers in sanitation industry based on the final criteria with fuzzy VIKOR
    Keywords: Sanitation Supply Chain, Agile Supply Chain, Fuzzy VIKOR
  • Isa Nakhai Kamalabadi *, Mohammad Mohammadnejad, Ramin Sadeghian, Fardin Ahmadizar Pages 29-40
    Mathematical models have been used in many areas of supply chain management. In this paper, we present a mixed-integer non-linear programing (MINLP) model to solve a multi-period, closed-loop supply chains (CLSCs) with two echelons consist of producers and customers. In order to satisfy the demands, the producers are be able to order for materials in the beginning of each period for one or more periods. A fleet of heterogeneous vehicles are routed to deliver the products from producers to customers and to pick up defective products from the customers and move them to the collection-repair center. Also, it is assumed that the rate of defective products is related to the price. In the other words, the more expensive product, the less rate of defect. The objective function maximize the profit which comes from total cost which is subtracted from income. The income is divided two part, selling products and wastes, and total cost consists of several part such as, costs of defective products, ordering cost, cost of holding in producers and collection-repair center, transportation costs, and the cost of assigning place for collection-repair center. Finally, computational results are discussed and analyzed for a numerical example in order to demonstrate the effectiveness of the proposed model.
    Keywords: Closed, loop supply chain, Mathematical modeling, Heterogeneous vehicles routing, Inventory, Pricing
  • Mahdi Eghbali *, Mohammad Saidi Mehrabad, Hassan Haleh Pages 41-46
    Scheduling is an important subject of production and operations management area. In flow-shop scheduling, the objective is to obtain a sequence of jobs which when processed in a fixed order of machines, will optimize some well defined criteria. The concept of transportation time is very important in scheduling. Transportation can be done by robots. In situations that robots are used to transport materials (material handler), breakdown of the machines and robots have a significant role in the production concern. This paper deals with minimization of the total elapsed time for flow shop scheduling problem (number of machine=3) in which the effect of machine and robots breakdown interval are considered simultaneously. Furthermore, by providing an example, the proposed algorithm is described. A summary and future works conclude the paper
    Keywords: scheduling problems, robots, break down interval, flow shop
  • Masoumeh Rahimi, Amir Najafi * Pages 47-57
    Customer satisfaction is the most important step in the process of identifying customer expectations. Identify customer expectations ‮without referring to him and get his view, is impossible. In order to identify customer expectations, service suppliers are also using ‮statistical techniques, surveyed their customers. According to the studies, there is no appropriate framework for expectation model to ‮prioritize regions of organizations and make the favorable selection according to the organization’s policies and strategies. In this ‮research, a combination of fuzzy multiple criteria decision making is used for the optimal selection. The research method used in this ‮study is of descriptive and applied type, and field method is used to collect data. For Identifying customer expectations, data has ‮been collected from study population (customers of Zanjan municipality) is 303 people through random sampling method. To ranking ‮the dimensions of customer's expectations and make optimal selections of municipality zones, data has been collected from study ‮population (engineer contractor of the municipality) is 30 people. The data collection instrument was questionnaire and interview, which ‮had been valid. The Expert Choice, Web-based TOPSIS, SPSS and Excel software were used for calculations. It is interesting to ‮observe that the choices of the best municipality zone solely depend on the criterion having the maximum priority value. Based on ‮calculations on the stages of the proposed model, "municipality Zone 2" was selected as the optimal the region and had the highest rating ‮in response to customer expectations. Results show that the proposed model has a systematic fit with the defined procedures and known ‮inputs.‮
    Keywords: Customer expectations, Multi Criteria Decision Making, Fuzzy Analysis Network Process (FANP), Fuzzy TOPSIS method, Fuzzy ELECTRE method
  • Mehdi Yazdani *, Bahman Naderi Pages 59-66
    Although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the problem of scheduling no-idle hybrid flow shops. A mixed integer linear programming model is first developed to mathematically formulate the problem. Using commercial software, the model can solve small instances to optimality. Then, two metaheuristics based on variable neighborhood search and genetic algorithms are developed to solve larger instances. Using numerical experiments, the performance of the model and algorithms are evaluated.
    Keywords: Scheduling, No, idle hybrid flow shops, Mixed Integer Linear Programming, Variable neighborhood search, Genetic algorithm
  • Ashkan Hafezalkotob, Kaveh Khalili, Damghani *, Seyed Sajad Ghashami Pages 67-78
    In this paper, a multi-objective multi-period multi-product supply chain network design problem is introduced. This problem is modeled using a multi-objective mixed integer mathematical programming. The objectives are maximizing the total profit of logistics, maximizing service level, and minimizing inconsistency of operations. Several sets of constraints are considered to handle the real situations of three-echelon supply chains. As the optimum value of conflictive objective functions of the proposed model cannot be met concurrently, so a goal programming approach is used. An illustrative numerical example is provided to show the mechanism of proposed model and the solution procedure. In a numerical example, 1 manufacture, 2 warehouses, 2 distribution centers (DCs), and 2 types of final products are considered in a planning horizon consists of 3 time periods. Products are shipped from the manufacturer to warehouses and then are shipped from the two warehouses to two distribution centers. The distribution centers are the point from which the product are shipped to final consumers. The Model is coded using GAMS software on a Core i7 CPU, using 8GB of RAM with MS-Windows 8.0. The optimum design of supply chain, inventory level for warehouses and distributors, and amount of shipments between echelons are determined.
    Keywords: Supply chain network design, Goal programming, Back order, Multi, Period Planning
  • Javad Hasanpour *, Mohammad Ghodoosi, Zahra Sadat Hosseini Pages 79-92
    The aim of a multi-mode resource-constrained project scheduling problem (MRCPSP) is to assign resource(s) with the restricted capacity to an execution mode of activities by considering relationship constraints, to achieve pre-determined objective(s). These goals vary with managers or decision makers of any organization who should determine suitable objective(s) considering organization strategies. We also introduce the preemptive extension of the problem which allows activity splitting. In this paper the preemption multi-mode resource-constrained project scheduling problem (P-MMRCPSP) with Minimum makespan and the maximization of net present value (NPV) has been considered. Since the considered model is NP-Hard, The performance of our proposed model is evaluated by comparison with two well-known algorithms; non-dominated sorting genetic algorithm (NSGA II), multi-objective imperialist competitive algorithm (MOICA). These metaheuristics have been compared on the basis of a computational experiment performed on a set of instances obtained from standard test problems constructed by the ProGen project generator, where, additionally, cash flows were generated randomly with the uniform distribution. Since the effectiveness of most meta-heuristic algorithms significantly depends on choosing the proper parameters. A Taguchi experimental design method (DOE) was applied to set and estimate the proper values of GAs parameters for improving their performances. The computational results show that the proposed MOICA outperforms the NSGA-II.
    Keywords: Multi, objective Project Scheduling, Resource Constraint, Preemptive, Net Present Value, Meta, heuristic Algorithm
  • Arghavan Sharafi, Mahdi Bashiri * Pages 93-100
    Over the two last decades, distribution companies have been aware of the importance of paying attention to the all aspects of a distribution system simultaneously to be successful in the global market. These aspects are the economic, the environmental, the social and the safety aspects. In the Vehicle Routing Problem (VRP) literature, the economic issue has often been used, while the environmental, the safety and the social concerns have been less proportion of studies. The Green vehicle routing problem (GVRP) is one of the recent variants of the VRP, dealing with environmental aspects of distribution systems. In this paper, two developed mixed integer programming models are presented for the GVRP with social and safety concerns. Moreover, a Genetic Algorithm (GA) is developed to deal efficiently with the problem in large size. Different numerical analyses have performed to validate the presented algorithm in comparison to exact solutions and investigate the influence of several key factors like the effect of increasing the cost of safety aspect on route balancing, and customer waiting time. The results confirm that the proposed algorithm performs well and has more social and safety benefits (such as more balanced tours and fewer customers waiting time than the classic GVRP.
    Keywords: Logistics, Distribution management, Green Vehicle Routing Problem, Route Balancing, Mixed Integer Linear Programming, Genetic algorithm