|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Title:||A Multi-Objective Simulated Annealing for Bus Driver Rostering|
|Citation:||Peng K, Shen Y & Li J (2015) A Multi-Objective Simulated Annealing for Bus Driver Rostering. In: Gong M, Pan L, Song T, Tang K & Zhang X (eds.) Bio-Inspired Computing -- Theories and Applications: 10th International Conference, BIC-TA 2015 Hefei, China, September 25-28, 2015, Proceedings. Communications in Computer and Information Science, 562. 2015 International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA2015), Hefei, China, 25.09.2015-28.09.2015. Berlin: Springer, pp. 315-330. http://link.springer.com/chapter/10.1007/978-3-662-49014-3_29; https://doi.org/10.1007/978-3-662-49014-3_29|
|Series/Report no.:||Communications in Computer and Information Science, 562|
|Conference Name:||2015 International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA2015)|
|Conference Dates:||2015-09-25 - 2015-09-28|
|Conference Location:||Hefei, China|
|Abstract:||This paper presents a Multi-Objective Simulated Annealing (MOSA) approach for noncyclic bus driver rostering. A heuristic is first devised to construct an initial solution. Next, a SA-based feasibility repairing algorithm is designed to make the solution feasible. Finally, a SA-based non-dominated solution generating algorithm is devised to find the Pareto front based on the feasible solution. Differing from previous work on the problem, the MOSA provides two options to handle user preferences: one with a weighted-sum evaluation function encouraging moves towards users’ predefined preferences, and another with a domination-based evaluation function encouraging moves towards a more diversified Pareto set. Moreover, the MOSA employs three strategies, i.e. incremental evaluation, neighbourhood pruning and biased elite solution restart strategy, to make the search more efficient and effective. Experiments show that the MOSA can produce a large number of solutions that reconcile contradictory objectives rapidly, and the strategies can enhance the computational efficiency and search capability.|
|Status:||VoR - Version of Record|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|Peng-et-al-BICTA-2015.pdf||Fulltext - Published Version||317.25 kB||Adobe PDF||Under Embargo until 3000-08-31 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.