Books: A Mathematical Programming-based Scheduling Framework For Multitasking Environments [An Article From: European Journal Of Operational Research] : Mathematical Enterprises

Math Book Categories

A mathematical programming-based scheduling framework for multitasking environments [An article from: European Journal of Operational Research]
enlarge	Authors: S. Shakeri, R. Logendran Publisher: Elsevier Category: Book Buy New: $7.95 as of 7/30/2010 13:08 MDT details Seller: Amazon.com Format: HTML Media: Digital ASIN: B000PAUK46 Publication Date: January 1, 2007 Availability: Available for download now



Editorial Reviews: Product Description This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser. Description: A new paradigm along with a mixed (binary) integer-linear programming model is developed for scheduling tasks in multitasking environments, for which the number of completed tasks is not a good measure. One special case falls into the realm of deteriorating jobs. Polynomial time optimal solution algorithms are presented for this and one other special case. As the complexity of the original problem is believed to be strongly NP-hard, an efficient solution algorithm, based on tabu search, is developed to solve the problem. Small, medium, and large size problems are solved, and the solution obtained from the algorithm is compared with that of the optimal solution or the upper bound found from using the Lagrangian relaxation. Where it was measurable, the search algorithm gave quantifiably good quality solutions, and in all cases it had a much better time efficiency than the branch-and-bound enumeration method. A detailed statistical experiment, based on the split-plot design, is developed to identify the characteristics of the tabu search algorithm, thus guaranteeing a solution that is significantly better in quality. A conjecturing technique is introduced for problems with very large planning horizons. This technique had remarkable time efficiency with no apparent loss of quality.

CERTAIN CONTENT THAT APPEARS ON THIS SITE COMES FROM AMAZON SERVICES LLC. THIS CONTENT IS PROVIDED ‘AS IS’ AND IS SUBJECT TO CHANGE OR REMOVAL AT ANY TIME.