DECISIONS AND OPERATIONS RESEARCH
Year:2018 | Volume:3 | Issue:2 |Papers Count:7

In managing a project,reliable prediction is an essential element for success.Project managers are always looking for controlling their projects to make sure the the project is within acceptable limits.For a long time,the earned value management (EVM) for pursuing time performance and the cost of the project has been used.However,using this method to valuate project time performance by utilizing the time performance index (SPI) by researchers and practitioners has been faced with serious criticism.Therefore,the present study proposes a framework for assessment and prediction of the temporal performance of each of the thread activities in project management.In this framework,using the multi objective league championship algorithm (MOLCA),the initial plan of the projects is optimized and then via using the Kalman Filter prediction method,project execution planning is done such that the projects in conditions of uncertainty could be forecasted and ahead horizon being demonstrated accurately with the least error for project managers.In this paper,in order to ensure the quality of the solutions,the output of the algorithm is compared with genetic algorithms (NSGII) and particle swarm optimization (MOPSO),where results demonstrate the superiority of the proposed algorithm.

Todays, meeting the healthcare needs of patients at home has many benefits. By providing regular and timely healthcare servicing, in addition to reducing costs, the patient's recovery process also speeds up. In this paper, a multi-depot vehicle routing problem is considered with regard to time windows and fuzzy demands. This paper attempts to optimize provided mathematical formulation in such a way that the distance traveled, total travel time, the number of transportation vehicles and transportation cost be minimized; also by taking the hard time window to meet patients, patient satisfaction rate will increase. This is a complex and difficult problem, and it takes a long time to solve it through linear programming and existing software. Therefore, in this paper, two general approaches including genetic algorithm and particle swarm optimization are used to tackle the problem. The response surface methodology (RSM) has been used to set parameters for meta-algorithms. To illustrate the efficiency of proposed algorithms, a number of test problems are solved and computational results are compared with the solutions obtained with the GAMS software.

In this paper, a multi-commodity planning problem with fixed-cost that is a special type of fixed charge transportation problem is developed. The proposed model determines the amount of products in the existing routes with the aim of minimizing the total cost to satisfy the demand of each customer. As the problem is NP-hard, a moderate sized instance of this problem becomes intractable for general-purpose solvers. In order to overcome this difficulty, a Lagrangian relaxation approach is proposed. The computational experiments show that the Lagrangian relaxation algorithm is able to solve large sized problems with optimality gap compared to general-purpose solvers.

In recent decades, as a result of the global economic growth and the development of investment, extensive researches have been carried out in the field of ranking companies, Data Envelopment analysis (DEA) and Analytical Hierarchy Process (AHP ) are the most important methods in this field, However, perhaps the most notable method is DEA/AHP which is, in fact, the combination of the mentioned ones. This method utilizes the strengths of DEA and AHP to rank the decision-making units (DMUs) in a company. The aim of this study is to provide a rating of cement companies operating in the stock using improved methods DEA / AHP is. The results of the research show that in 1391, Isfahan, Bojnoord and Qaen cement companies took the first to third places, but in 1392 these places belonged to Abyek, Isfahan and Cazroon companies. Therefore, it can be concluded that while using the improved integrated DEA and AHP method, not only the companies with higher efficiency are placed in higher ranks, but also, the inefficient companies are ranked effectively.

When dealing with international and overseas markets, corporate executives face somewhat complex strategic tasks related to the risk, stability, and potential returns of markets in the world. Selection from various international markets for export, concessions, joint venture and. . . needs information from the country and the target market. The evaluation of information in different types of market factors determines the extent of success in the international arena. Foreign market information can be derived from a combination of industry, market, and types of transactions. In this research, efforts have been made to investigate the effective factors and their prioritization on the decision-making on the export of Smart Cards of Sa-Iran to international countries. This research is applied in terms of purpose and descriptive-survey nature. To test the research hypotheses and obtain the results, SPSS software, one sample T test and Friedman test were used. The results of the hypothesis test showed that the factors affecting the decision making of exports by Sa-Iran to international countries are as follows: 1) legal environment; 2) political factor; 3) culture; 4) economic factor; 5) infrastructure.

This article shows that Operations research techniques play an important role in the development researches of financial and investment, and in recent years, with significant improvements in terms of the availability of real-time data and the speed of computer, this role has increased and in line with it by creating more opportunities for these techniques, more importance has been given to research and output. Given the importance of the issue today, there is a two-way relationship between financial concepts and investment with operational research techniques, that is, as various techniques of research in operations for financial affairs have been used, financial theories also require the development and improvement of solution Operations research techniques. The present paper shows that depending on the type of decision making in the field of finance and investment through research results, these techniques, in addition to raising the accuracy of the results of financial research, can lead to a greater variety of research, especially for the fields Financial engineering.

Inverse parabolic problems are the most famous ill-posed problems. Thus using stable inexact numerical methods for approximating these problems, causes a large perturbation. In this paper, we study the problem of determining the source term of the inverse source problem [{partial _t}T(x, t) = kappa, {nabla ^2}T(x, t) + g(t)delta (x-{x^*}), x in {( circ, , 1)^d}, t in ( circ, , {t_f}), ] from the measured data given in the form of [T({x_{measure}}, {t_i}) = {y_i}, , i = 1, 2, ldots, I, ] (additional condition) where d = 1, 2 and [delta ] is the Dirac delta function and (T, g) are the unknown functions. Then, using the statistical spline model and applying Levenberg-Marquardt method, we obtain an approximate solution for quasi solution g=g(t). Finally, to show the priority and accuracy of the introduced method some numerical examples are given.