A robust bi-objective mathematical model for disaster rescue units allocation and scheduling with learning effect

Date

2020-11-01

Author

Tirkolaee, Erfan Babaee
Aydin, Nadi Serhan
Ranjbar-Bourani, Mehdi
Weber, Gerhard Wilhelm

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

243
views

0
downloads

This paper proposes a novel bi-objective mixed-integer linear programming (MILP) model for allocating and scheduling disaster rescue units considering the learning effect. When a natural phenomenon (e.g., earthquake or flood) occurs, the presented decision support model is expected to help decision-makers of emergency relief centers to provide efficient planning for rescue units to minimize the total weighted completion time of rescue operations, as well as the total delay in rescue operations. The problem has some features in common with unrelated parallel machine scheduling (UPMS) problem and traveling salesman problem (TSP). To deal with the inherent uncertainty and bi-objective nature of the problem, an uncertainty-set based robust optimization technique and multi-choice goal programming (MCGP) with utility functions are applied. To demonstrate the applicability of the proposed model, a real case study in Mazandaran province in Iran is presented. The computational results confirm the high complexity of the problem and the significant impacts of the uncertainty on the solution. Moreover, the analytical results provide useful insights to decision-makers for disastrous situations.

Subject Keywords

General Engineering, General Computer Science

URI

https://hdl.handle.net/11511/69633

Journal

COMPUTERS & INDUSTRIAL ENGINEERING

DOI

https://doi.org/10.1016/j.cie.2020.106790

Collections

Graduate School of Applied Mathematics, Article

Suggestions

OpenMETU
Core

A unifying grid approach for solving potential flows applicable to structured and unstructured grid configurations Cete, A. Ruhsen; Yuekselen, M. Adil; Kaynak, Uenver (Elsevier BV, 2008-01-01) In this study, an efficient numerical method is proposed for unifying the structured and unstructured grid approaches for solving the potential flows. The new method, named as the "alternating cell directions implicit - ACDI", solves for the structured and unstructured grid configurations equally well. The new method in effect applies a line implicit method similar to the Line Gauss Seidel scheme for complex unstructured grids including mixed type quadrilateral and triangle cells. To this end, designated al...
Integrating estimation of distribution algorithms versus Q-learning into Meta-RaPS for solving the 0-1 multidimensional knapsack problem Arin, Arif; Rabadi, Ghaith (Elsevier BV, 2017-10-01) Finding near-optimal solutions in an acceptable amount of time is a challenge when developing sophisticated approximate approaches. A powerful answer to this challenge might be reached by incorporating intelligence into metaheuristics. We propose integrating two methods into Meta-RaPS (Metaheuristic for Randomized Priority Search), which is currently classified as a memoryless metaheuristic. The first method is the Estimation of Distribution Algorithms (EDA), and the second is utilizing a machine learning a...
girdap: Open source object-oriented autonomous grid management library for solving equations of conservation laws Uzgoren, Eray (Elsevier BV, 2017-10-12) girdap is an object-oriented grid generation and management library that uses finite volume operator objects to provide researchers and educators a framework to solve different sets of algebraic and differential equations on multiple grid objects, which are allowed to interact with each other. Grid objects have the capability of performing local anisotropic grid refinement (h-adaptation) as well as relocating their vertices (r-adaptation) to resolve length scales based on solution field obtained using algeb...
Beam search algorithm for capacity allocation problem in flexible manufacturing systems Ozpeynirci, Selin Bilgin; Azizoğlu, Meral (Elsevier BV, 2009-05-01) This study considers the operation assignment and tool allocation problem in flexible manufacturing systems. A set of operations together with their required tools are selected so as to maximize the total weight. The machines have limited time and tool magazine capacities and the tools are available in limited quantities. We develop a beam search algorithm and obtain near optimal solutions for large size problems very quickly.
Optimal scope of work for international integrated systems Ertem, Mustafa Alp; Serpil, Canan; Department of Industrial Engineering (2005) This study develops a systems integration project scheduling model which identifies the assignment of activity responsibilities that minimizes expected project implementation cost, considering the project risk. Assignment of resources to the individual jobs comprising the project is a persistent problem in project management. Mostly, skilled labor is an essential resource and both the time and the cost incurred to perform a job depend on the resource to which job is assigned. A systems integration project i...

Citation Formats

E. B. Tirkolaee, N. S. Aydin, M. Ranjbar-Bourani, and G. W. Weber, “A robust bi-objective mathematical model for disaster rescue units allocation and scheduling with learning effect,” COMPUTERS & INDUSTRIAL ENGINEERING, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69633.