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Jawad Abusalama
Universiti Teknikal Malaysia Melaka

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Dynamic real-time capacity constrained routing algorithm for evacuation planning problem Jawad Abusalama; Sazalinsyah Razali; Yun-Huoy Choo; Lina Momani; Abdelrahman Alkharabsheh
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i3.pp1388-1396

Abstract

Usually, disasters occur over a relatively short time anytime and anywhere. Most occupancies do not have absolute knowledge about the prevention or safety consciousness to deal with disasters. During disaster occurrence, evacuation processes are conducted to save people’s life, and if there is no appropriate evacuation plan, the situation will become worse. Thus, finding an optimal planning technique to evacuate occupants is critical in many cases i.e. emergency evacuation. In this paper, a Dynamic Real-Time Capacity Constrained Routing (DRTCCR) Algorithm has been proposed and analyzed. Such algorithm will investigate the capacity constraints of the evacuation network in real time by modelling the capacities based on time series to improve current solutions of the Emergency Route Planning (ERP) problem.  Such algorithm will produce an optimal solution for the ERP problem. Performance evaluation on many network models illustrates that the DRTCCR algorithm improves the previous evacuation planning by reducing the evacuation time as well as the computational cost. In addition, DRTCCR algorithm has the ability to recalculate and find out the optimal path dynamically in real time irrespective of the number of trapped people as well as the transportation network size. Analytical experiments have been carried out, which illustrates the efficiency of the proposed algorithm.
An enhanced approach for solving winner determination problem in reverse combinatorial auctions Jawad Abusalama; Sazalinsyah Razali; Yun-Huoy Choo
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp934-945

Abstract

When a disaster occurs, the single agent does not have complete knowledge about the circumstances of the disaster. Therefore, the rescue agents should coordinate with each other to perform their allocated tasks efficiently. However, the task allocation process among rescue agents is a complex problem, which is NP-complete problem, and determining the rescue agents that will perform the tasks efficiently is the main problem, which is called the winner determination problem (WDP). This paper proposed an enhanced approach to improve rescue agents’ tasks allocation processes for WDP in reverse combinatorial auctions. The main objective of the proposed approach is to determine the winning bids that will perform the corresponding tasks with minimum cost. The task allocation problem in this paper was transformed into a two-dimensional array, and then the proposed approach was applied to it. The main contribution of the proposed approach is to shorten the search space size to determine the winners and allocate the corresponding tasks for a combination of agents (i.e., more than two agents). The proposed approach was compared to the genetic algorithm regarding the execution time, and the results showed good performance and effectiveness of the proposed approach.
Co-Authors Abdelrahman Alkharabsheh Lina Momani Sazalinsyah Razali Yun-Huoy Choo