While a great portion of the scheduling literature focuses on time-based criteria, the most important goal of management is maximizing the profitability of the firm. In this paper, the net preset value criterion is studied taking account of linear time-dependent cash flows in single machine and flow shop scheduling problems. First, a heuristic method is presented for the single machine scheduli...

Branch-and-bound is a widely used method in combinatorial optimization, including mixed integer programming, structured prediction and MAP inference. While most work has been focused on developing problem-specific techniques, little is known about how to systematically design the node searching strategy on a branch-and-bound tree. We address the key challenge of learning an adaptive node search...

Branch-and-price is a well established technique for solving large scale integer programming problems. This method combines the standard branch-and-bound framework of solving integer programming problems with Column Generation. In each node of the branch-and-bound tree, the bound is calculated by solving the LP relaxation. The LP relaxation is solved using Column Generation. In this report, we ...

We present methods that are useful in solving some large scale hierarchical planning models involving 0-1 variables. These 0-1 programming problems initially could not be solved with any standard techniques. We employed several approaches to take advantage of the hierarchical structure of variables (ordered by importance) and other structures present in the models. Critical, but not sufficient ...

We present a branch-and-bound framework to solve the following problem: Given a graph G and an integer k, find a subgraph of G formed by removing no more than k edges that contains the most symmetry. We call symmetries on such a subgraph “almost symmetries” of G. We implement our branch-and-bound framework in PEBBL to allow for parallel enumeration and demonstrate good scaling up to 16 cores. W...

Abstract The paper proposes the formulation of a single-task robot (ST), single-robot task (SR), time-extended assignment (TA), multi-robot allocation (MRTA) problem with multiple, nonlinear criteria using discrete variables that drastically reduce computation burden. Obtaining an is addressed by Branch and Bound (B&B) algorithm in low scale problems genetic (GA) specifically developed for ...

This paper describes what is termed the "generalized assignment problem". It is a generalization of the ordinary assignment problem of linear programming in which multiple assignments of tasks to agents are limited by some resource available to the agents. A branch and bound algorithm is developed that solves the generalized assignment problem by solving a series of binary knapsack problems to ...

The facility location problem is a strategic decision-making for a supply chain, which determines the profitability and sustainability of its components. This paper deals with a scenario where two supply chains, consisting of a producer, a number of distribution centers and several retailers provided with similar products, compete to maintain their market shares by opening new distribution cent...

This article presents an exact cooperative method for solving the Multidimensional Knapsack Problem (MKP ) which combines dynamic programming and branch and bound. The first step of our algorithm tries to find out a good feasible solution of the (MKP ) using surrogate relaxation. For this purpose, we have developed a modified dynamic programming algorithm. The second step is based on a branch a...

Dual heuristics have been successfully used to generate bounds in the context of branch and bound algorithms. In the current work, we present a new dual heuristic for the set partitioning problem. Our approach provides a lower bound at each node of the branch and bound tree by calculating approximate solutions to the dual of the linear relaxation of the set partitioning problem. The calculation...