Abstract
The purpose of this paper is twofold. First, it introduces a new hybrid computational intelligence algorithm to the optimization community. This novel hybrid algorithm has hyperheuristic (HH) neighborhood search movements embedded into a recently introduced migrating birds optimization (MBO) algorithm. Therefore, it is called HHMBO. Second, it gives the necessary mathematical model for a shift scheduling problem of a manufacturing company defined by including the fairness perspective, which is typically ignored especially in manufacturing industry. Therefore, we call this complex optimization problem fairness oriented integrated shift scheduling problem (FOSSP). HHMBO is applied on FOSSP and is compared with the well-known simulated annealing, hyperheuristics, and classical MBO algorithms through extended computational experiments on several synthetic datasets. Experiments demonstrate that the new hybrid computational intelligence algorithm is promising especially for large sized instances of the specific problem defined here. HHMBO has a high exploration capability and is a promising technique for all optimization problems. To justify this assertion, we applied HHMBO to the well-known quadratic assignment problem (QAP) instances from the QAPLIB. HHMBO was up to 14.6% better than MBO on converging to the best known solutions for QAP benchmark instances with different densities. We believe that the novel hybrid method and the fairness oriented model presented in this study will give new insights to the decision-makers in the industry as well as to the researchers from several disciplines.
Highlights
Workforce scheduling has been a subject of continued research and commercial interest in several disciplines due to its important practical applications within the context of intelligent systems
If N is the size of a quadratic assignment problem (QAP) instance, we limited the run time with N3 iterations. is corresponded to 0.01 s for a problem of size 12 and to 48 s for a problem of size 100 on the specified machine
The minimum costs obtained in 10 runs are considered, since the aim is to check the ability of HHMBO in finding best known solutions (BKS)
Summary
Workforce scheduling has been a subject of continued research and commercial interest in several disciplines due to its important practical applications within the context of intelligent systems. Workforce scheduling is a concept that embraces a variety of scheduling problems, referred to as manpower scheduling and personnel scheduling in the literature. Constructing efficient and equitable schedules is a challenging issue requiring time and labor cost for the companies with high number of employees. E real world problem we tackled aims to provide fair personnel work schedules for a large-scale manufacturing company that works 24 hours and seven days a week. Personnel requirements for each day and shift differ and are updated periodically. Employee requirement changes every four weeks, regularly. There is a high rate of employee circulation. Erefore, possible maximum level of fairness within each planning period is sought. Ere are some essential legal regulations for employee schedules which make the problem much more complicated.
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