Genetic Algorithms: A Mature Bio-inspired Optimization Technique for Difficult Problems-Reference-Cited by-同舟云学术

Genetic Algorithms: A Mature Bio-inspired Optimization Technique for Difficult Problems

Published:2020 Issue: Volume: Page:3-25
ISSN:2196-7326
Container-title:Nature-Inspired Methods for Metaheuristics Optimization
language:
Short-container-title:

Author:

Katsifarakis Konstantinos L.,Kontos Yiannis N.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-26458-1_1

Reference31 articles.

1. Bhattacharjya RK, Datta B (2005) Optimal management of coastal aquifers using linked simulation optimization approach. Water Resour Manag 19:295–320

2. Coello CAC, Cortés NC (2004) Hybridizing a genetic algorithm with an artificial immune system for global optimization. Eng Optim 36(5):607–634

3. Dasgupta D, Michalewicz Z (eds) (1997) Evolutionary algorithms on engineering applications. Springer, Berlin/Heidelberg/New York

4. Deb K, Anand A, Joshi D (2002) A computationally efficient evolutionary algorithm for real-parameter evolution. Evol Comput 10(4):371–395

5. Eshelman LJ, Schaffer JD (1993) Real-coded genetic algorithms and interval schemata. In: Whitley DL (ed) Foundation of genetic algorithms II. Morgan Kaufmann, San Mateo, pp 187–202

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effects of pumping flow rates on the estimation of hydrogeological parameters;Journal of Hydroinformatics;2023-03-28

2. Genetic Algorithms-Based Optimum PV Site Selection Minimizing Visual Disturbance;Sustainability;2022-10-04

3. Cost minimization of groundwater supply to a central tank;Water Supply;2021-09-07