A Genetic Algorithm for a Workforce Scheduling and Routing Problem

Algethami, Haneen; Pinheiro, Rodrigo Lankaites; Landa-Silva, Dario

Abstract

The Workforce Scheduling and Routing Problem refers to the assignment of personnel to visits across various geographical locations. Solving this problem demands tackling scheduling and routing constraints while aiming to minimise the total operational cost. This paper presents a Genetic Algorithm (GA) tailored to tackle a set of real-world instances of this problem. The proposed GA uses a customised chromosome representation to maintain the feasibility of solutions. The performance of several genetic operators is investigated in relation to the tailored chromosome representation. This paper also presents a study of parameter settings for the proposed GA in relation to the various problem instances considered. Results show that the proposed GA, which incorporates tailored components, performs very well and is an effective baseline evolutionary algorithm for this difficult problem.

Citation

Algethami, H., Pinheiro, R. L., & Landa-Silva, D. (2016). A Genetic Algorithm for a Workforce Scheduling and Routing Problem.

• Conference Name: IEEE Congress on Evolutionary Computation (IEEE CEC 2016)
• End Date: Jul 29, 2016
• Acceptance Date: Apr 15, 2016
• Publication Date: Jul 25, 2016
• Deposit Date: Sep 13, 2016
• Publicly Available Date: Sep 13, 2016
• Peer Reviewed: Peer Reviewed
• Keywords: Genetic Algorithms, Indirect Solution Representation, Genetic Operators, Workforce Scheduling and Routing
• Public URL: https://nottingham-repository.worktribe.com/output/799547
• Related Public URLs: www.wcci2016.org/
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• Contract Date: Sep 13, 2016