Multistage decision-making using simulated annealing applied to a fuzzy automaton

2002 ◽  
Vol 2 (2) ◽  
pp. 140-151 ◽  
Author(s):  
Jiri Pospichal ◽  
Vladimir Kvasnicka
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 117063-117079
Author(s):  
Marta Lilia Erana-Diaz ◽  
Marco Antonio Cruz-Chavez ◽  
Rafael Rivera-Lopez ◽  
Beatriz Martinez-Bahena ◽  
Erika Yesenia Avila-Melgar ◽  
...  

2017 ◽  
Vol 67 (5) ◽  
pp. 529 ◽  
Author(s):  
Petr Stodola ◽  
Jan Mazal

<p>The model of optimal cooperative reconnaissance as a part of the tactical decision support system to aid commanders in their decision-making processes is presented. The model represents one of the models of military tactics implemented in the system to plan the ground reconnaissance operation for the commander optimally. The main goal of the model is to explore the area of interest by multiple military elements (scouts, UAVs, UGVs) as quickly as possible. A metaheuristic solution to this problem which combines two probabilistic methods: simulated annealing and the ant colony optimisation algorithm is proposed. In the first part of this study, the optimal cooperative reconnaissance problem is formulated. Then, metaheuristic solution, which is composed of three independent steps, is presented. Finally, experiments are conducted to verify the approach to this problem.</p>


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 131577-131592 ◽  
Author(s):  
Tinghua Ai ◽  
Rui Xin ◽  
Xiongfeng Yan ◽  
Min Yang ◽  
Bo Ai

Author(s):  
Alzira Mota ◽  
Paulo Ávila ◽  
Ricardo Albuquerque ◽  
Lino Costa ◽  
João Bastos

Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.


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