جستجوی مقالات مرتبط با کلیدواژه "meta-heuristic" در نشریات گروه "مدیریت"

The purpose of this research is to investigate the impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess returns of investment funds. In terms of method, the current research is a part of correlation research. In correlation research, the researcher's effort is focused on discovering or determining the relationship between one or more variables. In fact, the purpose of this method is to study the limits of changes of one or more variables with the limits of changes of one or more variables, and from the point of view of the purpose of this research, it is an applied research, the results of which can be useful for shareholders, stock exchange officials, and researchers. It is useful and in terms of the type of post-event studies that examines hypotheses based on past financial data. The statistical population of this research includes all the companies admitted to the Tehran Stock Exchange during the period of 36 months in the period from April 2019 to March 2011, which number is 591 companies based on the Rahevard software. According to the conditions and application of the aforementioned restrictions, 150 companies were selected as a sample in the 36 months ending in March 1401. By observing the results of the stock portfolio selection models with single and combined measures, we find that in all three models, the amount of risk increases with the increase in return. This shows that investors, in order to obtain more return, They are forced to accept

In this paper, a fuzzy goal single facility location problem under to asymmetric Linex loss function is discussed. The aim of this paper is to determine the location of a facility center in the ideal radius to each of the demand points. In general, such a response is not always available. Therefore, minimizing the error function obtained from the distance of facility center to the ideal point is desirable. As, in many real-life situations, positive error and negative error of the same size often have different economic and material implications, a asymmetric Linex loss function is used for the first time where distinguishes between positive and negative errors with the same distance. In this paper, first, this problem is first investigated in a definite manner and by proving a theorem it is shown that the problem has a feasible solution and the optimal solution of the problem lies in the expanded rectangular shell of the demand points. In the following, To determine the optimal solution of the problem, a gradient quasi-Weisfield algorithm is presented, and by proposing some theorems, it is shown that this algorithm is convergent to the optimal solution of the problem. Also, to confirm the accuracy of the results obtained from this method, the obtained results are compared with the metaheuristic colonial competition algorithm. Finally, for the first time, the problem is modeled in fuzzy mathematical mode, and using a three-objective genetic algorithm its answers are compared and analyzed with a definite model.

Transportation system brings the problem of vehicle routing that seeks optimal allocation of customers to vehicles in distribution system. There are various types of vehicle routing problems that try to provide models that are closer to the real world constraints by considering limitations such as vehicle capacity, number of demands, distance and so forth. The transportation network of Digikala Company inside and between cities is complicated based on the number of available routes, variety of means of transport and multiple distribution centers in the provincial areas. Digikala's distribution network is not only a geometric representation of the transport routes, but also represents the transport system. In this research, studying variables of shipping these goods has been considered, firstly, to identify a mathematical model for the distribution of these goods and then to examine how to solve this mathematical model, which is estimative and accurate. We solved this problem after examining and proving the model solution through approximate ways using meta-heuristic method which gives us the closest answers in NP-hard problems. Finally, while coding in small-scale Matlab software, we study the distribution model of the company and obtain the required output by proving the downward trend of the final function. The study confirms that online store companies can design, optimize, and manage complex supply chain operations at different levels with the help of Genetic Algorithm

In this paper we consider the inverse of backup 2-median problem. In this problem, a set of weighted points are given and we should change some parameters of the problem such as weights of vertices and edges and coordinates of points such that the two given points be the backup 2-median. We present mathematical models for inverse backup 2-median problems on graphs. In the case that the underlying network is a tree, linear models are presented for the problem with variable edges and weight of vertices. We also consider the continuous case of the problem with variable coordinates of vertices on the plane. In this case, we solve the model by PSO and a hybrid improved PSO methods. Computational results are compared for the varying amounts of parameters.   The inverse and backup location facility problems are two important branches of location theory that have been interested by many researchers in the recent decades.   Let n weighted points be given in the plane or on a graph. The inverse median models investigate to change some parameters of problem such as coordinates, edge lengths and vertex weights such that the given facilities be the median points. For more information about inverse location problems see Burkard et al. (2004). On the other hand, in the backup median problems supposed that some facilities may failed. Therefore the other facilities should serve the clients. The backup 2-median problem on trees has been considered by Wang et al. (2009). Fathali (2014) investigated the backup multi-facility location problem on the plane.
In this paper we consider the combination of inverse location and backup facility location problems. We want to change coordinates, weight of vertices or length of edges with minimum cost such that the given facilities be backup median facilities.  2. inverse Backup 2-Median On Trees: Let T= (V, E)  be a tree with n vertices. Each vertex  has a nonnegative weight. Let  be the distance between two points  and,  and  be the two given vertices in T which are assumed the location of facilities.   Each facility may fail with a probability. For any vertex, suppose that the cost of increasing and decreasing per unit of  is  and, respectively. Let  and  be the amounts by which the weight is increased and decreased, respectively. Then, the model of inverse backup 2-median problem can be written as follows. In this paper we investigated the backup 2-median problem with variable edge lengths and vertices weights on trees. The problem with variable coordinates on the plane is also considered. The models of mentioned problems and computational results which obtained by two PSO methods are presented.

In this paper minimization of total tardiness with intermediate due dates in flow shop scheduling is presented. There are some situations in which there is a due date for each intermediate operation of a job such as research and development and consulting projects. Usually each project (job) is carried out through different phases (machines) and there is an associated due date for each phase. Thus the tardiness of each phase should be considered. Due to the complex nature of the tardiness in flow shop problems and since this problem is a NP-hard, three Meta heuristic approaches; Simulated Annealing, Genetic Algorithm and Particle Swarm Optimization have been applied to reach near optimal solution. Extensive computational experiments are performed on 96 generated scenarios. Two indicators were used to evaluate the Meta heuristics. The results indicate that Simulated Annealing and Genetic Algorithm presented better solutions for the given scheduling problem. Moreover considering the CPU time, Genetic Algorithm provided the solution in less time.