A mixed integer programming approach to multi-skilled workforce scheduling

Cuevas, Rodolfo; Ferrer, Juan Carlos; Klapp, Mathias A.; Muñoz, Juan-Carlos

doi:10.1007/s10951-015-0450-0

Cited by 35 publications

(10 citation statements)

References 44 publications

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“…A subfield of personnel scheduling that is relevant for the problem addressed in this paper, is the field of multi-skilling problems, where each worker has a set of predefined skills that enable them to carry out a certain subset of the available tasks. Cuevas et al (2016), e.g., propose a mixed integer program for the short-term multi-skilled workforce tour scheduling problem, where workers' shifts and days off are planned while assigning activities to shifts. De Bruecker et al (2018) propose a three stage MIP approach for optimizing skill mix and training schedules for aircraft maintenance personnel.…”

Section: Related Workmentioning

confidence: 99%

Adaptive large neighborhood search for a personnel task scheduling problem with task selection and parallel task assignments

Gutjahr¹,

Parragh²,

Tricoire³

2023

Preprint

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Motivated by a real-world application, we model and solve a complex staff scheduling problem. Tasks are to be assigned to workers for supervision. Multiple tasks can be covered in parallel by a single worker, with worker shifts being flexible within availabilities. Each worker has a different skill set, enabling them to cover different tasks. Tasks require assignment according to priority and skill requirements. The objective is to maximize the number of assigned tasks weighted by their priorities, while minimizing assignment penalties. We develop an adaptive large neighborhood search (ALNS) algorithm, relying on tailored destroy and repair operators. It is tested on benchmark instances derived from real-world data and compared to optimal results obtained by means of a commercial MIP-solver. Furthermore, we analyze the impact of considering three additional alternative objective functions. When applied to large-scale company data, the developed ALNS outperforms the previously applied solution approach.

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Section: Related Workmentioning

confidence: 99%

Adaptive large neighborhood search for a personnel task scheduling problem with task selection and parallel task assignments

Gutjahr¹,

Parragh²,

Tricoire³

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Fırat and Hurkens [15] presented a task scheduling problem, in which complex tasks have multi-level skill requirements and technicians have varied capabilities. Cuevas et al [16] proposed a mixed integer programming approach to handle the multi-skilled workforce scheduling problem in service industry and concluded that employee multi-skilling is a significant source of labor flexibility to improve the coverage of labor requirements. On the other hand, the employee flexibility is commonly processed in terms of full-time contract and part-time employment.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

2020

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The order assignment in the food delivery industry is of high complexity due to the uneven distribution of order requirements and the large-scale optimization of workforce resources. The delivery performance of employees varies in different conditions, which further exacerbates the difficulty of order assignment optimization. In this research, a non-linear multi-objective optimization model is proposed with human factor considerations in terms of both deteriorating effect and learning effect, in order to acquire the optimal solutions in practice. The objectives comprised the minimization of the operational cost in multiple periods and the workload balancing among multiple employees. The proposed model is further transformed to a standardized mixed-integer linear model by the exploitation of linearization procedures and normalization operations. Numerical experiments show that the proposed model can be easily solved using commercial optimization softwares. The results indicate that the variance of employee performance can affect the entire delivery performance, and significant improvement of workload balancing can be achieved at the price of slight increase of the operational cost. The proposed model can facilitate the decision-making process of order assignment and workforce scheduling in the food delivery industry. Moreover, it can provide managerial insights for other labor-intensive service-oriented industries.

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“…For some small-sized instances, LP-solvers have been used to solve rostering problems (e.g. Bard, Binici, & deSilva, 2003;Cuevas, Ferrer, Klapp, & Muñoz, 2016;Örmeci et al, 2014 ). Complex problems can be solved by using heuristics which combine local search and network flow techniques.…”

Section: Introductionmentioning

confidence: 99%

A graph-based formulation for the shift rostering problem

Lai

Leung

Dullaert

et al. 2020

European Journal of Operational Research

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A mixed integer programming approach to multi-skilled workforce scheduling

Cited by 35 publications

References 44 publications

Adaptive large neighborhood search for a personnel task scheduling problem with task selection and parallel task assignments

Adaptive large neighborhood search for a personnel task scheduling problem with task selection and parallel task assignments

Multi-Objective Optimization for Order Assignment in Food Delivery Industry with Human Factor Considerations

A graph-based formulation for the shift rostering problem

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