A global optima search field division method for evolutionary algorithms-Reference-Cited by-同舟云学术

A global optima search field division method for evolutionary algorithms

Published:2021-04-13 Issue: Volume: Page:1-20
ISSN:0160-5682
Container-title:Journal of the Operational Research Society
language:en
Short-container-title:Journal of the Operational Research Society

Author:

Gharoie Ahangar Reza¹,Pavur Robert¹,Gharavi Hani²

Affiliation:

1. Department of Information Technology and Decision Sciences, G. Brint Ryan College of Business, University of North Texas, Denton, TX, USA

2. School of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, UK

Publisher

Informa UK Limited

Subject

Marketing,Management Science and Operations Research,Strategy and Management,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/01605682.2021.1890531

Reference80 articles.

1. Multi-objective biased randomised iterated greedy for robust permutation flow shop scheduling problem under disturbances

2. Handbook of Evolutionary Computation

3. Baluja, S. (1995). An empirical comparison of seven iterative and evolutionary function optimization heuristics. Technical Report, CMU-CS, 95-193. Carnegie-Mellon University, Department of Computer Science.

4. A Cooperative Approach to Particle Swarm Optimization

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