Citation
iSchedule, an Optimisation Toolkit for Complex Scheduling. In proceedings of the 3rd Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2007), 28 -31 August 2007, Paris, France, pages 344-352, 2007.
Paper
Abstract
Most of real-world scheduling problems which include optimisation and feasibility aspects, are NP-hard. To tackle large scale optimization problems, meta-heuristic algorithms are often proposed to quickly obtain near-optimal solutions. However, they have difficulty to find feasible solutions on strongly constrained problems, whereas constraint programming can help as they efficiently handle feasibility problems. Moreover, despite their success, these methods often require complete re-implementation to solve new problems or variations of the same problem. To address these issues, the Framework approach of the intelligent Optimization Toolkit iOpt [5] provides three components for problem modelling, solving and visualizing, based on constraints and meta-heuristic algorithms. The problem representation is well-matched to heuristic search operations, thanks to the use of an invariants processing engine. As a consequence it reduces the time necessary to develop efficient solutions. Extensions of iOpt have been developed for specific domains. Such an extension is the iSchedule Toolkit which is dedicated to assist non-expert users in modelling scheduling applications. This paper outlines iSchedule capabilities and illustrates their use on a particular scheduling problem, the mobile Workforce Scheduling problem, a Vehicle Routing-type problem with time windows, additional tasks and resource constraints, multiple concurrent objectives and subject to disturbances. This problem is of interest to BT in its field service operations.
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Bibtex
@INPROCEEDINGS{2007-344-352-P, author = {A. Liret and D. Lesaint and R. Dorne and C. Voudouris},
title = {iSchedule, an Optimisation Toolkit for Complex Scheduling},
booktitle = {In proceedings of the 3rd Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2007), 28 -31 August 2007, Paris, France},
year = {2007},
editor = {P. Baptiste and G. Kendall and A. Munier-Kordon and F. Sourd},
pages = {344--352},
note = {Paper},
abstract = {Most of real-world scheduling problems which include optimisation and feasibility aspects, are NP-hard. To tackle large scale optimization problems, meta-heuristic algorithms are often proposed to quickly obtain near-optimal solutions. However, they have difficulty to find feasible solutions on strongly constrained problems, whereas constraint programming can help as they efficiently handle feasibility problems. Moreover, despite their success, these methods often require complete re-implementation to solve new problems or variations of the same problem. To address these issues, the Framework approach of the intelligent Optimization Toolkit iOpt [5] provides three components for problem modelling, solving and visualizing, based on constraints and meta-heuristic algorithms. The problem representation is well-matched to heuristic search operations, thanks to the use of an invariants processing engine. As a consequence it reduces the time necessary to develop efficient solutions. Extensions of iOpt have been developed for specific domains. Such an extension is the iSchedule Toolkit which is dedicated to assist non-expert users in modelling scheduling applications. This paper outlines iSchedule capabilities and illustrates their use on a particular scheduling problem, the mobile Workforce Scheduling problem, a Vehicle Routing-type problem with time windows, additional tasks and resource constraints, multiple concurrent objectives and subject to disturbances. This problem is of interest to BT in its field service operations.},
owner = {user},
timestamp = {2012.05.21},
webpdf = {2007-344-352-P.pdf} }