Research Article
Year 2020,
Volume: 8 Issue: 4, 221 - 225, 31.12.2020
Abstract
Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.
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Year 2020,
Volume: 8 Issue: 4, 221 - 225, 31.12.2020
Abstract
References
- Inefficiency In European Airspace (Rep.). Iata Economic Briefing., 2013
- PingSong Dong , Dong Li, PaulDrake, Multi-Objective Optimization for a Liner Shipping Service from Different Perspectives, Transportation Research Procedia, Volume 25, 2017.
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- Bayrak, A. E., (2010), “Optimization Algorithms For Resource Allocation Problem Of Air Tasking Order Preparation”, in partial fulfillment of the requirements for the degree of master of science in computer engineering, Ortadoğu Teknik Üniversitesi
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- Zheng, D.X.M., Ng, T. S. T., and Kumaraswamy, M. M., Applying genetic algorithms techniques for time-cost optimization, Proc., 18th Annual Conf. ARCOM, D. Greenwood, ed., University of Northumbria, Middleborough, U.K., September 2-4, 2002, pp. 801-810.
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- John R. Birge and Francois Louveaux. Introduction to Stochastic Programming. Springer, 1997.
- G. Laporte, F.V. Louveaux, and H. Mercure. Priori optimization of the probabilistic traveling salesman problem. Operations Research, 42:3:543-549, 1994.
- B. Verweij, S. Ahmed, A.J. Kleywegt, G. Nemhauser, and A. Shapiro. The sample average approximation method applied to stochastic routing problems: a computational study. Computational Optimization and Applications, 24:289-333, 2003.
There are 19 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Research Article |
| Authors | |
| Publication Date | December 31, 2020 |
| Published in Issue | Year 2020 Volume: 8 Issue: 4 |
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