Robust Optimization for Handling Time Uncertainty in Capacitated V ehicle R outing P roblem for Post Disaster Aid Logistical Distribution
Audi Luqmanul Hakim Achmad1, Diah Chaerani2, Eman Lesmana3
1Luqmanul Hakim Achmad, Department of Mathematics, Universitas Padjadjaran, Sumedang, Indonesia.
2Diah Chaerani, Department of Mathematics, Universitas Padjadjaran, Sumedang, Indonesia.
3Eman Lesmana, Department of Mathematics, Universitas Padjadjaran, Sumedang, Indonesia.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 571-577 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6340018520/2020©BEIESP | DOI: 10.35940/ijrte.E6340.018520
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In post-disaster aid logistical distribution, time is the most important thing to minimize the number of victim. But, time travelling become uncertain as the impact of disaster occurrence. In this paper, Robust Capacitated Vehicle Routing Problem (RCVRP) for post-disaster aid logistical distribution under time uncertainty is discussed to handle the uncertain travelling time. The robust optimal solution derivation is presented using Robust Optimization. The time uncertainty is assumed to be lied in a box and a polyhedral uncertainty set. This assumption yields a Robust Counterpart (RC) of the RCVRP model which are computationally tractable. Case study and simulation presented in this paper and shows a robust optimal solution.
Keywords: Box and Polyhedral Uncertainnty, Capacitated Vehicle Routing Problem, Computational Tractability, Robust Optimization.
Scope of the Article: Cross Layer Design and Optimization.