Abstract

Abstract The Skilled Workforce Project Scheduling Problem (SWPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many company Service Centres (SC). The SWPSP considers many real characteristics faced daily by the SC: client-company service quality agreements that establish maximum dates for the beginning and the end of tasks with penalties for delays, criticality levels indicating the client-priority in processing each task, generalized precedence relationships that can produce cycle structures, time period and percentage time lags and variable task durations depending on the worker executing the task. Furthermore, the SC workforce is made up of specialist workers characterised by efficiency levels showing their efficiency and speed executing the several types of tasks. Each worker has his or her own timetable. The main objective of the SWPSP is to quickly obtain a feasible plan of action satisfying maximum established dates and timetable worker constraints. Secondary objectives deal with the urgency levels imposed by the criticality task levels, to obtain well-balanced worker workloads and an efficient assignment of specialists to tasks. In this paper an efficient and quick hybrid genetic algorithm that combines local searches with genetic population management techniques is presented to manage the model.

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