فهرست مطالب

Iranian Journal Of Operations Research
Volume:4 Issue: 1, 2013

  • تاریخ انتشار: 1392/12/01
  • تعداد عناوین: 7
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  • Moeen-Moghadas, Monabbati, Taghizadeh-Kakhki Pages 1-13
    Since late 1960''s, the emergency location problems, fire stations and medical emergency services have attracted the attention of researchers. Mathematical models, both deterministic and probabilistic, have been proposed and applied to find suitable locations for such facilities in many urban and rural areas. Here, we review some models proposed for finding the location of such facilities, with an eye on successfully implemented real life applications. We then propose an extension of the QM-CLAM model of Marianov and Serra (1998) to M/G/k systems, and suggest a GRASP type heuristic procedure for solving the problem. To improve the computed solution, local search heuristics are used. Sensitivity analysis and some computational results are also presented.
    Keywords: Emergency location problems, Maximal covering location problems, Queueing location models, GRASP
  • Karamali, Memariani, Jahanshahloo Pages 14-24
    Here, we examine the capability of artificial neural networks (ANNs) in sensitivity analysis of the parameters of efficiency analysis model, namely data envelopment analysis (DEA). We are mainly interested to observe the required change of a group of parameters when another group goes under a managerial change, maintaining the score of the efficiency. In other words, this methodology provides a platform for simulating the level of some parameters against the remaining parameters for generating different scenarios, as being in demand for managers.
    Keywords: Data envelopment analysis (DEA), Artificial neural networks (ANN), Sensitivity analysis
  • Khalili, Tavakkoli-Moghaddam Pages 25-38
    We relax some assumptions of the traditional scheduling problem and suggest an adapted meta-heuristic algorithm to optimize efficient utilization of resources and quick response to demands simultaneously. We intend to bridge the existing gap between theory and real industrial scheduling assumptions (e.g., hot metal rolling industry, chemical and pharmaceutical industries). We adapt and evaluate a well-known algorithm based on electromagnetic science. The motivation behind our proposed meta-heuristic approach has arisen from the attraction-repulsion mechanism of electromagnetic theories in physics. In this basic idea, we desire to bring our search closer to a region with a superior objective function while going away from the region with the inferior objective function in order to move the solution gradually towards optimality. The algorithm is carefully evaluated for its performance against two existing algorithms using multi-objective performance measures and statistical tools. The results show that our proposed solution method outperforms the others.
    Keywords: Performance quality measures, Traditional scheduling problem, Multi objective optimization, No intermediate queues
  • Morovatdar, Aghaie, Roghanian, Asl Haddad Pages 39-54
    We consider criticality in project networks having imprecise activity duration times. It is well known that finding all possibly critical paths of an imprecise project network is an NP-hard problem. Here, based on a method for finding critical paths of crisp networks by using only the forward recursion of critical path method, for the first time an algorithm is proposed which can find all possibly critical paths of interval-valued project networks. The proposed algorithm considers interactivity among paths which has not been yet considered in the fuzzy project scheduling literature. The extension of the proposed algorithm to the fuzzy network calculates criticality degrees of activities and paths of projects without any need to enumerate all project paths. Although algorithms for calculating criticality degrees in fuzzy networks have been previously proposed, despite the fact that they mostly consider a specific type of fuzzy numbers as activity duration times, the exiting algorithms do not discriminate possibly critical paths before calculating the criticality degrees. The computational experience on a series of well-known project samples confirms the algorithm to be remarkably more efficient than similar algorithms for fuzzy networks.
    Keywords: Project scheduling, Fuzzy PERT, Critical path, Imprecise network
  • Izadi, Ranjbarian, Ketabi, Nassiri-Mofakham Pages 55-74
    Among various statistical and data mining discriminant analysis proposed so far for group classification, linear programming discriminant analysis has recently attracted the researchers’ interest. This study evaluates multi-group discriminant linear programming (MDLP) for classification problems against well-known methods such as neural networks and support vector machine. MDLP is less complicated as compared to other methods and does not suffer from having local optima. This study also proposes a fuzzy Delphi method to select and gather the required data, when databases suffer from deficient data. In addition, to absorb the uncertainty infused to collecting data, interval MDLP (IMDLP) is developed. The results show that the performance of MDLP and specially IMDLP is better than conventional classification methods with respect to correct classification, at least for small and medium-size datasets.
    Keywords: Multi, group interval linear programming, Classification problem, Fuzzy Delphi feature selection
  • Krishnamoorthi Pages 75-87
    A product life cycle is the life span of a product in which the period begins with the initial product specification and ends with the withdrawal from the market of both the product and its support. A product life cycle can be divided into several stages characterized by the revenue generated by the product. This study investigates inventory control policies in a manufacturing system for a single product during the product life cycle, which consists of four stages: introduction, growth, maturity and decline. In all inventory models a general assumption is that products have indefinitely long lives. In general, almost all items deteriorate over time. Often, the rate of deterioration is low and there is little need to consider the deterioration in the determination of the economic lot size. The objective is to derive the cycle time and optimal production lot size to minimize total costs for the product life cycle with deteriorating items. The relevant model is built, solved and some main results on the uniqueness of the solution using rigorous mathematical methods are obtained. Illustrative examples are provided to verify our findings numerically.
    Keywords: Inventory, Product life cycle, Growth, maturity, Deteriorating items, Demand, production
  • Kheirfam Pages 88-107
    We present a new full Nesterov and Todd step infeasible interior-point algorithm for semi-definite optimization. The algorithm decreases the duality gap and the feasibility residuals at the same rate. In the algorithm, we construct strictly feasible iterates for a sequence of perturbations of the given problem and its dual problem. Every main iteration of the algorithm consists of a feasibility step and some centering steps. We show that the algorithm converges and finds an approximate solution in polynomial time. A numerical study is made for the numerical performance. Finally, a comparison of the obtained results with those by other existing algorithms is made.
    Keywords: Infeasible interior, point algorithm, Semi, definite optimization, Full Nesterov, Todd step, Polynomial time complexity