Mixed Integer Program Heuristic for Linear Ordering Problem

  title={Mixed Integer Program Heuristic for Linear Ordering Problem},
  author={Ehsan Iranmanesh and Ramesh Krishnamurti},
The Linear Ordering Problem is a classic optimization problem which can be used to model problems in graph theory, machine scheduling, and voting theory, many of which have practical applications. Relatively recently, there has been some success in using Mixed Integer Program (MIP) heuristic for NP-hard optimization problems. We report our experience with using a MIP heuristic for the problem. Our heuristic generates a starting feasible solution based on the Linear Programming solution to the… 

Tables from this paper

Primal Heuristic for the Linear Ordering Problem

A new primal heuristic is proposed for the Linear Ordering Problem (LOP) that generates an integer feasible solution from the solution to the LP relaxation at each node of the branch-and-bound search tree.

Supervised neighborhood selection and MIP-based primal heuristics

A supervised large neighborhood search heuristic for the general mixed integer programs and compare it with Relaxation Induced Neighborhood Search (RINS), a popular LNS heuristic, which not only finds an improving solution more often but also improves the solver performance on key metrics.

Algorithms for Problems in Voting and Scheduling

This dissertation studies the voting problem and the ranking problem in computational social choice, as well as a matching problem in a restricted graph, and shows how the linear program of this problem can be solved by using a primal-dual based combinatorial algorithm instead of the Simplex method.



The Linear Ordering Problem: Exact and Heuristic Methods in Combinatorial Optimization

This monograph details state-of-the-art optimization methods, both exact and heuristic, for the LOP to provide the reader with the background and practical strategies in optimization to tackle different combinatorial problems.

Local branching

This paper investigates the use of a generic MIP solver as a black-box ``tactical'' tool to explore effectively suitable solution subspaces defined and controlled at a ``strategic'' level by a simple external branching framework.

Exact and Approximate Nondeterministic Tree-Search Procedures for the Quadratic Assignment Problem

Two new techniques for solving the Quadratic Assignment Problem are introduced, one of which is a heuristic technique, defined in accordance with the Ant System metaphor, and includes as a distinctive feature the use of a new lower bound at each constructive step.

Effective Local and Guided Variable Neighbourhood Search Methods for the Asymmetric Travelling Salesman Problem

This paper proposes a hybrid of HyperOpt and 3-opt which allows to benefit from the advantages of both approaches and gain better tours overall, and introduces the notion of a "guided shake" within VNS and shows that this yields a heuristic which is more effective than the random shakes proposed by Hansen and Mladenovic.

A survey of very large-scale neighborhood search techniques

Combinations of Local Search and Exact Algorithms

The advantadges and disadvantages of local search and exact methods of solving NP-hard problems are described and why combining the two approaches is highly desirable.

Computers And Intractability A Guide To The Theory Of Np Completeness

Thank you very much for reading computers and intractability a guide to the theory of np completeness. As you may know, people have look hundreds times for their favorite novels like this computers

Computer solutions of the traveling salesman problem

Two algorithms for solving the (symmetric distance) traveling salesman problem have been programmed for a high-speed digital computer and are based on a general heuristic approach believed to be of general applicability to various optimization problems.

Table 2: Computational results for Instances RandAII