Multi-objective personnel scheduling problem with multiple qualification and client’s satisfaction: real case

Efficiently managing human resources scheduling is of great interest for industry decision-makers aiming to maintain a high service level and strategically organize employee work shifts, particularly those engaged in direct client interactions. This paper investigates the multi-skill personnel scheduling problem within the service industry, inspired by the recurring challenges faced by a technical control company in its daily operations. The context involves clients requesting specific services, each comprising interdependent tasks executed by inspectors with varying qualifications over one or more days. The overarching objective, within the context of a technical control company featuring a diverse team of inspectors and geographically dispersed tasks, is to optimize the scheduling of inspectors for a sequence of tasks. This optimization seeks to minimize workload, travels, premiums, and the radiation dose received by inspectors, taking into account the unique qualification requirements associated with each task. This paper presents a goal programming model designed for scheduling inspectors into control shifts. Recognizing the substantial computational effort required for real-world instances of the problem, a Greedy Randomized Adaptive Search Procedure metaheuristic is proposed to derive acceptable solutions. The performance of the proposed metaheuristic is demonstrated through application to real-life problem instances, showcasing its efficacy in addressing the intricacies of the multi-skill personnel scheduling problem in service industries.