in financial matters, portfolio can be interpreted as a combination or a series of investments hold by an institution or a person. portfolio optimization is one of the most important concerns of investors for maximizing the portfolio in financial markets. the formation of portfolio is a vital and critical decision for the companies.  in fact, the selection of portfolio is to specify the capital...

This paper addresses production-inventory problem for the manufacturer by explicitly taking into account multistage and varying demand. A nonlinear hybrid integer constrained optimization is modeled to minimize the total cost including setup cost and holding cost in the planning horizon. A genetic algorithm is developed for the problem. A series of computational experiments with different sizes...

This paper investigates the multistage hybrid flow shop (HFS) scheduling problems using the new bat algorithm. A HFS is the generalisation of flowshop with multiple machines. HFS is one of the important scheduling problems that represent many industries like iron and steel, chemical, textile and ceramic industries. The HFS scheduling problems have been proved to be NP-hard. A recently developed...

Multistage Interconnection Networks (MINs) are very popular in switching and communication applications. A MIN connects N inputs to N outputs and is referred as an N × N MIN; having size N. Optical Multistage Interconnection Network (OMIN) represents an important class of Interconnection networks. Crosstalk is the basic problem of OMIN. Switch Conflict and Link Conflict are the two main reason ...

In stochastic programming and decision analysis, an important issue consists in the approximate representation of the multidimensional stochastic underlying process in the form of scenario tree. This paper presents the approach to generate the multistage multidimensional scenario tree out of a set of scenario fans. For this purpose, the multistage K-means clustering algorithm is developed. The ...

multiple traveling salesman problem (mtsp) is one of the most popular operation research problem and is known as combinatorial optimization problems. mtsp is an extension version of the famous and widely used problem named traveling salesman problem (tsp). because of its benefices in various domains, many researchers have tried to solve that, and many methods have proposed so far. mtsp is a np-...

clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...