Optimising case study personnel scheduling problem using an artificial bee colony algorithm Online publication date: Thu, 01-Sep-2016
by Mayssa Koubâa; Sonda Elloumi; Souhail Dhouib
International Journal of Shipping and Transport Logistics (IJSTL), Vol. 8, No. 5, 2016
Abstract: The population-based meta-heuristics are usually inspired from nature and unlike to the local search meta-heuristics which bring in a unique solution, these algorithms are able to manipulate a group of acceptable solutions at each stage of the research process. Today, the population-based meta-heuristics are widely used for the optimisation of NP-hard problems. Among these meta-heuristics, the algorithm of the artificial bee colony ABC, which is inspired by the forage behaviour of the honey bee in nature. In this paper, we suggest to solve an NP-hard problem, consisting in seafaring staff scheduling within a Tunisian company by means of the ABC algorithm. The objective of this work is to provide the company with schedules guaranteeing improved staff rest levelling compared with that traditionally applied. Besides, the obtained results show the performance of the ABC algorithm in the improvement of the cover rate for the scheduling with regard to the already proposed methods in literature.
Online publication date: Thu, 01-Sep-2016
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