Computational experiments for local search algorithms for binary and mixed integer optimization

In this thesis, we implement and test two algorithms for binary optimization and mixed integer optimization, respectively. We fine tune the parameters of these two algorithms and achieve satisfactory performance. We also compare our algorithms with CPLEX on large amount of fairly large-size instances. Based on the experimental results, our binary optimization algorithm delivers performance that is strictly better than CPLEX on instances with moderately dense constraint matrices, while for sparse instances, our algorithm delivers performance that is comparable to CPLEX. Our mixed integer optimization algorithm outperforms CPLEX most of the time when the constraint matrices are moderately dense, while for sparse instances, it yields results that are close to CPLEX, and the largest gap relative to the result given by CPLEX is around 5%. Our findings show that these two algorithms, especially the binary optimization algorithm, have practical promise in solving large, dense instances of both set covering and set packing problems.

Department dc:contributor.department

Massachusetts Institute of Technology. Computation for Design and Optimization Program.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Zhou, Jingting, S.M. Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• Dimitris J. Bertsimas.

• Computation for Design and Optimization Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/61898

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/61898