ILP Model and Relaxation-Based Decomposition Approach for Incremental Topology Optimization inp-Cycle Networks
Author(s) -
Md. NoorEAlam,
Ahmed Zaky Kasem,
John Doucette
Publication year - 2012
Publication title -
journal of computer networks and communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 23
eISSN - 2090-715X
pISSN - 2090-7141
DOI - 10.1155/2012/546301
Subject(s) - survivability , network topology , computer science , decomposition , relaxation (psychology) , set (abstract data type) , topology (electrical circuits) , mathematical optimization , mathematics , computer network , psychology , social psychology , ecology , combinatorics , biology , programming language
p-cycle networks have attracted a considerable interest in the network survivability literature in recent years. However, most of the existing work assumes a known network topology upon which to apply p-cycle restoration. In the present work, we develop an incremental topology optimization ILP for p-cycle network design, where a known topology can be amended with new fibre links selected from a set of eligible spans. The ILP proves to be relatively easy to solve for small test case instances but becomes computationally intensive on larger networks. We then follow with a relaxation-based decomposition approach to overcome this challenge. The decomposition approach significantly reduces computational complexity of the problem, allowing the ILP to be solved in reasonable time with no statistically significant impact on solution optimality
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom