Journal of Operational Research in its Applications
Year:2014 | Volume:11 | Issue:3 (42)|Papers Count:8

Due to the importance of considering uncertainty in performance evaluation issues which arises in real world problems and their wide range of applications, in this paper, we propose a robust optimization approach to analyze this problem. We evaluate the relative efficiency of decision making units by data envelopment analysis method in which the input and output parameters have interval uncertainties. We consider robust counterpart of data envelopment analysis under interval uncertainties for inputs and outputs, and show that the dual of the robust counterpart of the envelopment form is equivalent to the optimistic counterpart of the multiplier form.

Nanotechnology has variant applications in food industries and their prioritizing is important for decision- making about the best allocation of different sources and the investing for accessing to developing markets of produces of Nano Technology in alimentary industries and their expanding. However, the problem is that how the prioritization of the applications in alimentary industries is done on the basis of combinational model of Multiple Criteria Decision Making (MCDM). To solve it by initial researches and scientific documents, the important criteria to prioritizing the most important applications of Nano Technology in alimentary industries are investigated, so the criteria that have the more decimal and fuzzy weightings are selected. Then, evaluation of the criteria is used by a binary comparisons questionnaire under uncertainty (fuzzy) conditions, and the responses of 10 specialists and by combinational method of ANP based on DEMATEL (DANP) and VIKORA for prioritization. The results of the prioritization show that the application of Nano Technology in "packing" and "quality control" levels of alimentary industry has more distinction, and it is on the priority. The results can help decision makers to improve the priorities and strategic programing.

The vehicle routing problem (VRP) is an important scientific problem addressed in distribution management. In classical VRP, the vehicle load is often regarded as a constant during transportation; therefore, the loading cost associated with the amount of the load on the vehicle, are neglected in the objective function when optimizing a vehicle routine. However, in real-world, the vehicle load varies from one customer to another in a vehicle route. Thus, the vehicle route without considering the effect of loading cost may lead to sub-optimal routes. In this paper, we investigate VRP with loading, which considers the costs associated with the amount of the load on the vehicle when determining the vehicle routes. This paper presents a new Pareto-based multi-objective approach that uses a Multi-objective Scatter search strategy for solving a multi-objective formulation of the VRP that aims to minimize the total distance of the vehicles used to service the customers, while also minimizing the imbalance of workloads (distances travelled/goods delivered by the vehicles). This new approach is evaluated in comparison with two well-known multi- objective algorithms, MOPSO and MODE. The results obtained when solving a subset of benchmark problems show the good performance of this approach. The results demonstrate that the suggested method is highly competitive.

This study aims at simulating the Loading and unloading system of Esfahan Steel Company’s store house of steel products and accordingly analyzing the practical solutions to decrease the stay and wait time of the trucks that arrive in the factory. According to the recorded time in the release and storage information of the factory’s system, loading lines were the most time-consuming sections, as a result this study focused on the existed lines. The study begins with timing the Docks and different stations to access the system’s factors which are under investigation. To simulate the system, ARENA 14 software was used. After validating the proposed model and confirming its validation, adding labor groups’ scenario will be made in order to reduce wait times.

Accidents and natural disasters and crises coming out of them indicate the importance of precise planning to combat them. Therefore, disaster relief logistics is one of the main activities in disaster management. In this paper, the response phase of disaster management cycle has been studied. A multi-objective model has been offered for location, vehicle routing and good distribution in damaged area in fuzzy conditions. This model includes uncertainty in handling time, amount of demand in damaged areas and inventories in suppliers in different periods. The model first priority is to minimize total arriving time to the damaged areas and maximize damaged areas satisfaction that can be achieved by maximizing the minimum ratio of total demand covered that ends in a kind of justice in good distribution and the second priority is to minimize costs. To solve the multi-objective model, the global criterion method has been used to produce a single objective model of multi-objective model. Finally, a case study has been done in South Khorasan.

This study aims to analyze technical efficiency and Water Use Efficiency (WUE) of date palm in Bahoukalat country from Chabahar, Iran. Data were gathered through questionnaires in 2010. To obtain WUE and technical efficiency, super efficiency and additive model were applied. The results showed that WUE is 40%. Moreover, 17 out of 23 date groves which are consumed traditional systems for irrigation were inefficient in water use. Furthermore, none of groves faced decreasing returns to scale and 78 % had increasing returns to scale. Therefore, due to economies of scale, there is a great potential to further increase of palm groves performance. Finally, calculating the amount of inefficiency for each factors of production showed an average of 23 percent inefficiency in water use.

Banking system is considered as an important component of the economy, and the market economy has a heavy responsibility to the recession, where growth and prosperity of the country or workmanship are closely related to banking institutions. In the present study to measure various aspects of bank branches in the province of Bushehr an integrated approach of DEA / AHP is used.This methodology uses a strong base of linear programming, it is possible that the proper evaluation of the units to be achieved, and appropriate basis for rational decisions for allocating resources to emerge. In this study, firstly, by using DEA models (using mathematical modeling and solving software Lingo) per branch a comparison is made with other branches, and then with the use of the results of matrix comparisons paired up with a solution AHP model, branches have been ranked completely. Matrix of paired comparisons based on DEA model is solved, for each pair of agents this approach is a quantitative one, however, the final ranking is done using a qualitative approach. The results show that in the period studied, Modares Branch ranked first and, and Safavi and Lian are located in the second and third ranks. The advantage of the proposed model is that, complete rankings branches under study; because the DEA method may focus on more than one branch, perfect performance can be achieved. In this case, ranking and distinguishing them is difficult. Thus, using a combination of approaches to solve this problem is proposed.

In this paper with the use of the B-spline parameterization, a new method based on the proposed modified hybrid genetic algorithm (MHGA), is introduced for solving a class of optimal control problems. In each iteration of the proposed algorithm, using uniform distribution of time interval, MHGA is run with a random initial population in which each individual item of the population is a matrix of control input values in time nodes of the partition. MHGA combines GA with SQP to be regarded as a local search. To decrease the computational time, in the beginning of the algorithm, a less number of integration for SQP is used, when the promising region of search space was found, we gradually increase the number of iterations of SQP. The optimal solution of MHGA is considered as the B-spline coefficients for the parameterization of the control. For better approximation of control curves in the next iteration, the number of time nodes are increased, and the above procedure is repeated. The algorithm is terminated when the norm of differences between two consecutive parameterized control curves or the differences of the objective function's value for two iteration is less than the prescribed numbers. To investigate the efficiency of the proposed algorithm, the numerical results are applied on more than ten optimal control problems.