The facility layout problem (FLP) is a wellresearched problem of finding positions of departments on a plant floor such that departments do not overlap and some specific critical criteria involved in FLP are optimized. In addition, the facility layout dramatically influences the efficiency of material handling within a manufacturing system. In order to ensure optimal performance within a manufacturing system, the facility layout should reflect changes throughout time. However, the static facility layout problem with constant material flows between departments may not be a realistic scenario because a manufacturing facility is a dynamic system that constantly evolves. On the other hand, layout problem has multi-objective nature, and it is necessary to apply various criteria and goals for determining a good facility layout. As a result, this research is about determining a solution for dynamic facility layout problem (DFLP) with equal departments by applying data envelopment analysis (DEA) with consideration of some specific criteria which are cost, adjacency, and distance requested. Cost as a negative criterion is minimized and used as an input, whereas adjacency and distance requested are considered positive criteria and used as output of DEA model. In the proposed algorithm, at first, the initial layout is generated, and then its neighborhood is created by the pair exchange and reverse strategy. By applying tabu search heuristic using diversification strategy which includes "frequency-based memory," "penalty function," and "dynamic tabu list size" to the DEA model, the most desired efficient layout is obtained. Two data sets taken from the relevant literature are used to test and evaluate the performance of the proposed heuristic. Computational experiments show that the proposed heuristic outperforms other heuristics presented in relevant literature, and the most efficient layout is achieved.
Capital budgeting investment decisions involve the use of a large portion of a firm’s assets; actually no decision places a company in more jeopardy than these decisions. Often these investments can cost billions of dollars, and require predictions of the future, without a suitable return the very existence of the company can be compromised. This paper aims to provide a review and analysisoncapital budgeting techniquesfrom 1970 to 2012 in developing and developed countries regarding the most effective factors on selecting techniques. It also analyzes how industries proceed to more sophisticated techniques during four decades. The most important flaws of traditional methods were criticized to analyze whether adopting a new sophisticated method like real option (RO) could eliminate them. Through an overview on RO domain and its process, the most efficient usageof sophisticated methodswas found.Reviewing previous empirical studies on real option adoptiongive us insight for providing required infrastructures before applying real option process. Our main aim by providing this paperis to help readers makethe most appropriate decision about capital budgeting techniques in terms of different factors with a great focus on real option (in the case which real option domain would not be contravened)and fault detecting to remove important obstacles and achieve successful real option implementation.
In this paper, we propose a multi criteria decision making technique to determine an efficient solution for quadratic assignment problem. The proposed method of this paper considers transportation cost, adjacency and separation as the most important criteria to find the efficient layout. A tabu search is used to generate a set of feasible solutions and for each solution, we evaluate various criteria. The proposed model of the paper uses DEA technique to choose the most efficient units among the feasible solutions. The implementation of the proposed method is demonstrated using some benchmark problems and the results are discussed in details.
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