Lifting-Automated Guided Vehicle (L-AGV) has been widely used in the fourth-generation automated port for its advantages on time-savings. Optimize the port L-AGV scheduling problem has dramatically significant impacts on port working efficiency. An improved Artificial Bee Colony algorithm (IABC) was proposed to greatly solve the problem by introducing ideas of genetic algorithm (GA) and adaptive factors. Compared with original Artificial Bee Colony algorithm (ABC) and GA, IABC made better performances on solutions and convergence, which also provided a direction on decision optimization for port AGV scheduling problem related.
An Improved Artificial Bee Colony Algorithm to Port L-AGV Scheduling Problems
01.07.2021
2116111 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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