Investigate The Potential And Limitations Of Meta-Heuristics Algorithms Applied In Reservoir Operation Systems
Creators: name: Othman, Faridah
name: Sadeghian, Mohammad Sadegh
name: Heydari, Mohammad
Publisher: name: Zenodo
Year: 2015
Subjects: meta-heuristics, Optimal Reservoir Operation, Genetic algorithms, Simulated Annealing

description: Nowadays, we are faced with the complex of process in water resource management. The complexity of water resources system makes the analysis of water resources investment alternatives difficult and complex. This leads to increase the application of systems analysis techniques. Optimization makes it possible to do exact mathematical modeling in a process, so by applying mathematical programming methods we will be able to optimize our models. Recently approximation algorithms are developed to combine the basic principles of heuristic algorithms to reach an efficient method in feasible region. These methods are known as meta-heuristic methods. Evolutionary algorithms (EAs), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Tabu Search (TS) and Artificial Neural Networks (ANN) are examples of these methods. The mathematical programming has two main problems. Sometimes they consider local optima points as global optimum points, and each of the mentioned methods is used for certain issues. In these studies the main focus is on developing tools to assist decision making and planning of water resources.<br>
The tools of systems analysis are varied in their usefulness. The approach and appropriate techniques naturally vary from problem to problem. It depends on the characteristics, i.e., the objective, scope of planning, state of development of system, the space and time of planning process. Our goal in this paper is to explain some advantages and disadvantages of meta-heuristic methods like genetic algorithm and simulated annealing algorithm in planning, limitations, and applications. Furthermore, we aim to note some points to apply the most ideal of using the programming methods in water resources systems optimization.
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