Planning production and working time within an annualised hours scheme framework

Production flexibility is essential for industrial companies that have to deal with seasonal demand. Human resources are one of the main sources of flexibility. Annualising working hours (i.e., the possibility of irregularly distributing the total number of working hours over the course of a year) is a tool that provides organisations with flexibility; it enables a firm to adapt production capacity to fluctuations in demand. However, it can involve a worsening of the staff’s working conditions. To take this into account, the planning and scheduling of working time should comply with constraints derived from the law or from a collective bargaining agreement. Thus, new and more difficult working-time and production planning and scheduling problems are arising. This paper proposes two mixed-integer linear program models for solving the problem of planning the production, the working hours and the holiday weeks of the members of a human team operating in a multi-product process in which products are perishable, demand can be deferred and temporary workers are hired to stand in for employees. The results of a computational experiment are presented.Peer Reviewe

Annualised Hours: A Real Flexibility Tool

Annualising working hours (AH) is a mean to face the seasonal nature of the demand. AH provides much flexibility to the production system, so the company is allowed to plan the staff working time more efficiently. However, the introduction of AH entails new optimisation problems to solve, as is the working time planning problem. These problems should be solved in an efficient way so AH could be a real and operative flexibility tool. Mixed and integer linear programming has been shown as a very effective approach in the resolution of some real and artificial generated AH problems.Peer Reviewe

Cost-efficient staffing under annualized hours

We study how flexibility in workforce capacity can be used to efficiently match capacity and demand. Flexibility in workforce capacity is introduced by the annualized hours regime. Annualized hours allow organizations to measure working time per year, instead of per month or per week. An additional source of flexibility is hiring employees with different contract types, like full-time, part-time, and min-max, and by hiring subcontractors. We propose a mathematical programming formulation that incorporates annualized hours and shows to be very flexible with regard to modeling various contract types. The objective of our model is to minimize salary cost, thereby covering workforce demand, and using annualized hours. Our model is able to address various business questions regarding tactical workforce planning problems, e.g., with regard to annualized hours, subcontracting, and vacation planning. In a case study for a Dutch hospital two of these business questions are addressed, and we demonstrate that applying annualized hours potentially saves up to 5.2% in personnel wages annually

Characteristics and classification of the annualised workings hours planning problems

Annualising working hours (i.e., the possibility of irregularly distributing throughout the year the total amount of the employees working hours) is one of the means to face the seasonal nature of the demand. Annualising working hours provides much flexibility to the production system (which is one of the main principles of lean production), so the company is allowed to plan the staff working time more efficiently. However, doing irregular working weeks implies a worsening of the working conditions that could be compensated by reducing the workers annual working time. On the other hand, conditions are provided in order to avoid an excessive workers’ overburden in long periods of strong demand. This paper introduces annualised hours (AH) as a mean to achieve production flexibility and proposes a classification scheme of the annualised working hours planning problems that arise in services and in manufacturing, as well as an approach for solving them by using mixed and integer linear programming and assessing the benefits of introducing AH.Peer Reviewe

Using a MILP model to establish a framework for an annualised hours agreement

Production flexibility is essential for industrial companies that have to deal with seasonal demand. Human resources are one of the main sources of flexibility. Annualising working hours (i.e., the possibility of irregularly distributing the total number of working hours over the course of a year) is a tool that provides flexibility to organizations; it enables a firm to adapt production capacity to fluctuations in demand. However, it can imply a worsening of the staff’s working conditions. To take the human aspect into account, the planning and scheduling of working time should comply with constraints derived from the law or from a collective bargaining agreement. Furthermore, new and more difficult working-time planning and scheduling problems are arising. This paper proposes a mixed-integer linear program model to solve the problem of planning the production and the working hours of a human team that operates in a multi-product process. Solving the model for different settings provides the essential quantitative information to negotiate the best conditions of the annualised hours system (the elements to establish the trade-off between weekly flexibility and economic or working-time reduction compensation can be obtained). The results achieved in a computational experiment were very satisfactory.Peer Reviewe

A scenario optimisation procedure to plan annualised working hours under demand uncertainty

Annualising working hours (i.e., the possibility of irregularly distributing the total number of working hours over the course of a year) enables to adapt production capacity to fluctuations in demand. The demand, which is an essential data for an optimal planning of work time, usually depends on several and complex factors. Often, tit is not possible to obtain a reliable prediction of the demand or it is no realistic to consider that can be adjusted to a probability distribution. In some cases, it is possible to determine a set of demand scenarios. Each one with a related probability. In this work we present a multistage stochastic optimization model which provides a robust solution (i.e., feasible for any possible scenario) and minimises the expected total capacity shortag

Optimal staffing under an annualized hours regime using Cross-Entropy optimization

This paper discusses staffing under annualized hours. Staffing is the selection of the most cost-efficient workforce to cover workforce demand. Annualized hours measure working time per year instead of per week, relaxing the restriction for employees to work the same number of hours every week. To solve the underlying combinatorial optimization problem this paper develops a Cross-Entropy optimization implementation that includes a penalty function and a repair function to guarantee feasible solutions. Our experimental results show Cross-Entropy optimization is efficient across a broad range of instances, where real-life sized instances are solved in seconds, which significantly outperforms an MILP formulation solved with CPLEX. In addition, the solution quality of Cross-Entropy closely approaches the optimal solutions obtained by CPLEX. Our Cross-Entropy implementation offers an outstanding method for real-time decision making, for example in response to unexpected staff illnesses, and scenario analysis

Capacity planning with working time accounts in services

This paper presents, formalises and classifies working time accounts (WTA’s), means of achieving flexible production capacity through the flexible organization of working time. We propose linear programming models to plan working time, using WTA, at companies in service industry. A computational experiment shows that the models can be solves for any planning problems of reasonable size

Gestión de los horarios de trabajo en presencia de cláusulas de flexibilidad pasiva.

La flexibilidad pasiva permite adaptar de forma eficiente y económica la capacidad de producción a las fluctuaciones de la demanda, pero genera una gran dificultad en la gestión de los horarios individuales así como la no aceptación de este tipo de sistemas por parte de los trabajadores. Se presentan dos modalidades de flexibilidad (jornada anualizada y cuentas de horas) y se muestra como, mediante herramientas de gestión de horarios adecuadas, es posible sacar el máximo partido de la flexibilidad manteniendo el respeto por las condiciones de los trabajadores.Peer Reviewe

Manpower Planning with Annualized Hours Flexibility: a Fuzzy Mathematical Programming Approach

We have considered the problem of Annualized Hours (AH) in workforce management. AH is a method of distributing working hours with respect to the demand over a year. In this paper the basic manpower planning problem with AH flexibility is formulated as a fuzzy mathematical programming problem with flexible constraints. Three models of AH planning problem under conditions of fuzzy uncertainty are presented using different aggregation operators. These fuzzy models softens the rigidity of deterministic model by relaxing some of the constraints using flexible programming. Finally, an illustration is given with a computational experiment performed on realistic scale case problem of an automobile company to demonstrate and analyze the effectiveness of the fuzzy approach over deterministic model