A hybrid algorithm Tabu Search – GRASP for wounded evacuation in disaster response

2020 ◽  
Vol 54 (1) ◽  
pp. 19-36
Author(s):  
Mohamad Khorbatly ◽  
Hamdi Dkhil ◽  
Hassan Alabboud ◽  
Adnan Yassine
Keyword(s):  
Tabu Search ◽  
Disaster Response ◽  
Hybrid Algorithm ◽  
Complex Problem ◽  
Informed Decision Making ◽  
Search Procedure ◽  
Adaptive Search ◽  
Resource Assignment ◽  
Negative Effects ◽  
Evacuation Plan

Natural and triggered-disasters, have devastating and profound negative effects on human lives that require a speedy declaration of an emergency in order to minimize their severe consequences. Hence, a prompt disaster response, in addition to effective measures such as informed decision making, organized evacuation plan, right hospital selection, proper rescue vehicles, efficient resources assignment and timely vehicle scheduling are critical actions needed to organize successful secured operations that could, if well prepared, save many injured bodies and lessen the human distress. To reach this ultimate goal, a complicated procedure should be in place and any failure can potentially increase the number of causalities, thus a complete alertness and full caution should be exercised. In this paper, we treat the Integrated Problem of Ambulance Scheduling and Resource Assignment (IPASRA) in the case of a sudden disaster. The main resources to be assigned are the ambulances and the hospitals. While, the hospitals serving capacities might be considered or not according to the extent of disaster and particularly to the wounded bodies’ total number. We formulate the (IPASRA) as a linear model, furthermore a novel hybrid algorithm based on Tabu Search (TS) and Greedy Randomized Adaptive Search Procedure (GRASP) is offered to tackle this complex problem. Simulation tests are also presented to prove the efficiency of our modelling and resolution approaches.

scholarly journals A Hybridalldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Ricardo Soto ◽  
Broderick Crawford ◽  
Cristian Galleguillos ◽  
Fernando Paredes ◽  
Enrique Norero
Keyword(s):  
Tabu Search ◽  
Hybrid Algorithm ◽  
Search Algorithm ◽  
Search Procedure ◽  
Global Constraint ◽  
Approximate Methods ◽  
Complete Collection ◽  
Robust Approach ◽  
Np Complete ◽  
Exact And Approximate Methods

The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling an2 × n2grid, composed ofncolumns,nrows, andnsubgrids, each one containing distinct integers from 1 ton2. Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with thealldifferentglobal constraint from the constraint programming world. Thealldifferentconstraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.

scholarly journals A Decision Model for Emergency Warehouse Location Based on a Novel Stochastic MCDA Method: Evidence from China

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Junkang He ◽  
Chenpeng Feng ◽  
Dan Hu ◽  
Liang Liang
Keyword(s):  
Disaster Response ◽  
Decision Model ◽  
Complex Problem ◽  
Decision Makers ◽  
Location Decision ◽  
Preference Information ◽  
Inaccurate Information ◽  
Country Level ◽  
Warehouse Location ◽  
Method Evidence

China is one of the disaster-prone countries in the world. Constructing a rapid and effective relief logistic system is important for disaster-responding at country level. Strategic prepositioning of emergency items, especially the decision of appropriate emergency warehouses location, has significant impacts on rapid disaster response to ensure sufficient relief supplies. The emergency warehouse location decision is a complex problem, where a wide variety of criteria need to be considered and the preference information of decision makers (DMs) may be imprecise or even absent. In this paper, we identify key effectiveness-oriented criteria used to evaluate the alternative emergency warehouse locations and make an attempt to propose a new multicriteria ranking method to solve the problem of inaccurate or uncertain weight information based on stochastic pairwise dominant relations and the pruning procedure of ELECTRE-II method. The proposed method extends the conventional ELECTRE-II method by incorporating inaccurate information and broadens its application to emergency warehouse location field. The feasibility and applicability of the proposed method are illustrated with a simulated example.

scholarly journals GASAT: A Genetic Local Search Algorithm for the Satisfiability Problem

2006 ◽  
Vol 14 (2) ◽  
pp. 223-253 ◽  
Author(s):  
Frédéric Lardeux ◽  
Frédéric Saubion ◽  
Jin-Kao Hao
Keyword(s):  
Tabu Search ◽  
Local Search ◽  
Hybrid Algorithm ◽  
State Of The Art ◽  
Search Algorithm ◽  
Satisfiability Problem ◽  
Local Search Algorithm ◽  
Overall Performance ◽  
Genetic Local Search ◽  
Search Stage

This paper presents GASAT, a hybrid algorithm for the satisfiability problem (SAT). The main feature of GASAT is that it includes a recombination stage based on a specific crossover and a tabu search stage. We have conducted experiments to evaluate the different components of GASAT and to compare its overall performance with state-of-the-art SAT algorithms. These experiments show that GASAT provides very competitive results.

scholarly journals Integrated Multi-Project Scheduling and Hierarchical Workforce Allocation in the ETO Assembly Process

2019 ◽  
Vol 9 (5) ◽  
pp. 885 ◽  
Author(s):  
Chun Jiang ◽  
Xiaofeng Hu ◽  
Juntong Xi
Keyword(s):  
Tabu Search ◽  
Project Scheduling ◽  
Hybrid Algorithm ◽  
Manufacturing Industry ◽  
Assembly Process ◽  
Solution Quality ◽  
Workforce Allocation ◽  
Benchmark Instances ◽  
Engineer To Order ◽  
Searching Ability

The engineer-to-order (ETO) production strategy plays an important role in today’s manufacturing industry. This paper studies integrated multi-project scheduling and hierarchical workforce allocation in the assembly process of ETO products. The multi-project scheduling problem involves the scheduling of tasks of different projects under many constraints, and the workforce allocation problem involves assigning hierarchical workers to each task. These two problems are interrelated. The task duration depends on the number of hierarchical workers assigned to the task. We developed a mathematical model to represent the problem. In order to solve this issue with the minimization of the makespan as the objective, we propose a hybrid algorithm combining particle swarm optimization (PSO) and Tabu search (TS). The improved PSO is designed as the global search process and the Tabu search is introduced to improve the local searching ability. The proposed algorithm is tested on different scales of benchmark instances and a case that uses industrial data from a collaborating steam turbine company. The results show that the solution quality of the hybrid algorithm outperforms the other three algorithms proposed in the literature and the experienced project manager.

scholarly journals Tabu search-based fleet scheduling of air ambulances for disaster response

Array ◽  
2020 ◽  
Vol 8 ◽  
pp. 100047
Author(s):  
Joseph Tassone ◽  
Salimur Choudhury
Keyword(s):  
Tabu Search ◽  
Disaster Response ◽  
Air Ambulances

scholarly journals A Hybrid Metaheuristic of Integrating Estimation of Distribution Algorithm with Tabu Search for the Max-Mean Dispersion Problem

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Dieudonné Nijimbere ◽  
Songzheng Zhao ◽  
Haichao Liu ◽  
Bo Peng ◽  
Aijun Zhang
Keyword(s):  
Tabu Search ◽  
Probability Model ◽  
Estimation Of Distribution Algorithm ◽  
Search Procedure ◽  
Hybrid Metaheuristic ◽  
Benchmark Instances ◽  
Conditional Preference ◽  
Estimation Of Distribution ◽  
Dispersion Problem ◽  
Move Operator

This paper presents a hybrid metaheuristic that combines estimation of distribution algorithm with tabu search (EDA-TS) for solving the max-mean dispersion problem. The proposed EDA-TS algorithm essentially alternates between an EDA procedure for search diversification and a tabu search procedure for search intensification. The designed EDA procedure maintains an elite set of high quality solutions, based on which a conditional preference probability model is built for generating new diversified solutions. The tabu search procedure uses a fast 1-flip move operator for solution improvement. Experimental results on benchmark instances with variables ranging from 500 to 5000 disclose that our EDA-TS algorithm competes favorably with state-of-the-art algorithms in the literature. Additional analysis on the parameter sensitivity and the merit of the EDA procedure as well as the search balance between intensification and diversification sheds light on the effectiveness of the algorithm.

scholarly journals Jobs scheduling within Industry 4.0 with consideration of worker’s fatigue and reliability using Greedy Randomized Adaptive Search Procedure

2019 ◽  
Vol 52 (19) ◽  
pp. 85-90
Author(s):  
I. El Mouayni ◽  
G. Demesure ◽  
H. Bril-El Haouzi ◽  
P. Charpentier ◽  
A. Siadat
Keyword(s):  
Industry 4.0 ◽  
Search Procedure ◽  
Adaptive Search
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