Workforce scheduling and routing problems: literature survey and computational study

Abstract

In the context of workforce scheduling, there are many scenarios in which personnel must carry out tasks at different locations hence requiring some form of transportation. Examples of these type of scenarios include nurses visiting patients at home, technicians carrying out repairs at customers' locations and security guards performing rounds at different premises, etc. We refer to these scenarios as Workforce Scheduling and Routing Problems (WSRP) as they usually involve the scheduling of personnel combined with some form of routing in order to ensure that employees arrive on time at the locations where tasks need to be performed. The first part of this paper presents a survey which attempts to identify the common features of WSRP scenarios and the solution methods applied when tackling these problems. The second part of the paper presents a study on the computational difficulty of solving these type of problems. For this, five data sets are gathered from the literature and some adaptations are made in order to incorporate the key features that our survey identifies as commonly arising in WSRP scenarios. The computational study provides an insight into the structure of the adapted test instances, an insight into the effect that problem features have when solving the instances using mathematical programming, and some benchmark computation times using the Gurobi solver running on a standard personal computer.

A genetic algorithm for a workforce scheduling and routing problem

“…The existence of connected activities gives raise to time-dependent activities constraints. A study by Castillo-salazar et al [8] applied a mixed integer programming (MIP) solver to tackle WSRP with time-dependent activities constraints. That study revealed that tackling instances with 50 activities or more required considerable computational time.…”

A Variable Neighbourhood Search for Nurse Scheduling with Balanced Preference Satisfaction

“…A solution requires all visits to be served hence it is not always possible to meet all visit requirements and workers availability. To evaluate the quality of a solution, the tier-based minimisation objective function shown in Equation (1) is utilised, which is employed by our industrial partner and also commonly used in the literature [16,2].…”

“…Solving this problem requires defining a schedule and a route plan for each worker such that all tasks (where possible) are covered. These problems combine features from both scheduling and routing problems, making them very challenging optimisation problems [1][2][3]. Examples of practical applications of WSRP are home healthcare scheduling [4,5], technician scheduling [6,7] and security personnel scheduling [8].…”

Mixed Integer Programming with Decomposition to Solve a Workforce Scheduling and Routing Problem

“…Common constraints (see also (Castillo-Salazar et al, 2014)) such as path constraint (2), skill and qualification (7) and time windows (9) form the basic structure of the scheduling and routing problem (Dantzig and Ramser, 1959;Bredstrom and Ronnqvist, 2008;Dohn et al, 2009;Castro-Gutierrez et al, 2011;Rasmussen et al, 2012). Tailor cut constraints adopted from literature are the availability constraints (10,11) while the constraints that required further adaptation to our problem features are the working region (13) (implemented as soft constraint) and startend paths (3-6).…”

“…(Castillo-Salazar et al, 2014). One specific example of WSRP is home health care services where nurses or care workers should deliver care services at the patient's home.…”