Binary goal programming model for optimizing tire selection using branch and bound algorithm

A Fuzzy Goal Programming Model for Efficient Portfolio Selection.

This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is propo...

A two-stage robust model for portfolio selection by using goal programming

In portfolio selection models, uncertainty plays an important role. The parameter’s uncertainty leads to getting away from optimal solution so it is needed to consider that in models. In this paper we presented a two-stage robust model that in first stage determines the desired percentage of investment in each industrial group by using return and risk measures from different industries. One rea...

A Branch and Bound Algorithm for Solving the Binary Bi-level Linear Programming Problem

A Branch and Bound Algorithm for Separable Concave Programming

In this paper, we propose a new branch and bound algorithm for the solution of large scale separable concave programming problems. The largest distance bisection (LDB) technique is proposed to divide rectangle into sub-rectangles when one problem is branched into two subproblems. It is proved that the LDB method is a normal rectangle subdivision(NRS). Numerical tests on problems with dimensions...

Fast Branch & Bound Algorithm in Feature Selection

We introduce a novel algorithm for optimal subset selection. Due to its simple mechanism for predicting criterion values the algorithm finds optimum usually several times faster than any other known Branch & Bound [5], [7] algorithm. This behavior is expected when the algorithm is used in conjunction with non-recursive and/or computationally expensive criterion functions.