By Topic

A general parallel simulated annealing library and its application in airline industry

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kliewer, G. ; Dept. of Math. & Comput. Sci., Paderborn Univ., Germany ; Tschoke, S.

To solve real-world discrete optimization problems approximately metaheuristics such as simulated annealing and other local search methods are commonly used. For large instances of these problems or those with a lot of hard constraints even fast heuristics require a considerable amount of computational time. At the same time, especially for sensitivity analyses, fast response times are necessary in real-world applications. Therefore, to speed up the computation a parallelization of metaheuristics is very desirable. We present parSA, an object-oriented simulated annealing library based on C++ and using the MPI message passing interface. It provides an automatic, transparent way of parallelizing simulated annealing. The efficient communication in parSA is the main reason for its success in several real-world applications. To demonstrate performance of parSA we address the weekly fleet assignment problem (FAP) as a real-world application. It is one of the optimization problems which occur in the process of operating an airline. Given a flight schedule and aircraft of different types (subfleets), to each flight leg a subfleet has to be assigned. Large real-world instances have been provided by internationally operating airlines. We show that our heuristic approach using our library parSA is very competitive to the commonly used integer-program (IF) approach

Published in:

Parallel and Distributed Processing Symposium, 2000. IPDPS 2000. Proceedings. 14th International

Date of Conference: