A Python/C plus plus library for bound-constrained global optimization using a biased random-key genetic algorithm

作者：Silva R M A; Resende M G C^*; Pardalos P M

来源：Journal of Combinatorial Optimization, 2015, 30(3): 710-728.

DOI：10.1007/s10878-013-9659-z

• Biased random-key genetic algorithm
• Global optimization
• Multimodal functions
• Continuous optimization
• Heuristic
• Stochastic algorithm
• Stochastic local search
• Nonlinear programming

This paper describes libbrkga, a GNU-style dynamic shared Python/C++ library of the biased random-key genetic algorithm (BRKGA) for bound constrained global optimization. BRKGA (J Heuristics 17:487-525, 2011b) is a general search metaheuristic for finding optimal or near-optimal solutions to hard optimization problems. It is derived from the random-key genetic algorithm of Bean (ORSA J Comput 6:154-160, 1994), differing in the way solutions are combined to produce offspring. After a brief introduction to the BRKGA, including a description of the local search procedure used in its decoder, we show how to download, install, configure, and use the library through an illustrative example.

• 出版日期2015-10