An effective artificial bee colony algorithm for the flexible job-shop scheduling problem (C++ implementation)
Implementation of a the artificial bee colony algorithm for solving the job shop sceduling problem
The Job Shop scheduling Problem (JSSP) is considered to be a problem belonging to the NP-difficult class. In this project, we have studied and implemented the work proposed by Wang et al. [1] which consists in minimizing the execution time (In the context of JSSP, this execution time is called "makespan") of a set of tasks on a certain number of machines. Each machine performs one operation at a time, and one operation continues to run on a machine until it is completed without interruption.
The Artificial Bee Colony algorithm is an evolutionary algorithm introduced by Karaboga and Basturk [2], which is inspired by the behavior of honey bees in their method of foraging. They implement a kind of collective intelligence (Swarm intelligence). Each bee has a specific role, and communicates with the other bees to locate food sources so as to collect more nectar in a reasonable time.
[1]: Wang, L., Zhou, G., Xu, Y. et al. An effective artificial bee colony algorithm for the flexible job-shop scheduling problem. Int J Adv Manuf Technol 60, 303–315 (2012). https://doi.org/10.1007/s00170-011-3610-1 [2]: Karaboga, D., & Basturk, B. (2007, June). Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In International fuzzy systems association world congress (pp. 789-798). Springer, Berlin, Heidelberg.