Branch and bound method for multiobjective pairing selection

Efficient Branch and Bound Methods for Pairing Selection

During the past few decades, a number of methods for selection of input-output pairings for decentralized control have been proposed. Most of these available methods require evaluation of every alternative in order to find the optimal pairings. As the number of alternatives grows rapidly with problem size, pairing selection through an exhaustive search can be computationally forbidding for larg...

Branch and bound method for regression-based controlled variable selection

Self-optimizing control is a promising method for selection of controlled variables (CVs) from available measurements. Recently, Ye et al. [2012] have proposed a globally optimal method for selection of self-optimizing CVs by converting the CV selection problem into a regression problem. In this approach, the necessary conditions of optimality (NCO) are approximated with linear combinations of ...

Constraint Optimization Techniques for MultiObjective Branch and Bound Search

A Branch and Bound Method for Finding Flow Path Designing of Agv Systems (RESEARCH NOTE)

One of the important factor in the design of automated guided vehicle systems (AGVS) is the flow path design. This paper presents a branch-and-bound algorithm to determining the flow path by considering not only loaded-vehicles, but also empty-vehicles. The objective is to find the flow path, which will minimize total travel of loaded vehicles. We know that in branch-and-bound method a branch c...

A Recursive Branch and Bound Algorithm for Feature Selection

Feature selection is a basic problem in pattern recognition application. The branch and bound (BB) algorithm is the only feature selection algorithm that provides global optimal results. All BB algorithms in literature are currently nonrecursive algorithms, and their corresponding program code is highly complex. In this study, a recursive BB algorithm, which is easy to program and debug, is des...