A Differential Evolution Algorithm for Military Workforce Planning Problems: A Simulation-Optimization Approach

Karam M. Sallam, Hasan Huseyin Turan, Ripon K. Chakrabortty, Sondoss Elsawah, Michael J. Ryan

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

Abstract

Appropriate workforce planning in an organization can ensure maximum profitability. Better way of planning and scheduling is also very important to avoid unexpected expenditures and high employee turnovers. This paper proposes a simulation-optimization approach to predispose the best strategic decisions for a long-term workforce planning problem by taking into account the complex interactions among many components (e.g., recruitment, attrition, promotion, training, and retention) of workforce planning. We use a differential evolution (DE) algorithm as the optimization method to couple with a system dynamics (SD) simulation model. The set of all feasible workforce planning policies is developed by the SD simulation and then searched by the DE algorithm while the fitness evaluation (i.e., total cost) of policies is evaluated by the simulation model. We demonstrate the approach through numerical experiments on a military workforce planning problem to provide insight into how the different strategies affect the overall system performance with regards to both total cost and fleet availability.

Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
EditorsHussein Abbass, Carlos A. Coello Coello, Hemant Kumar Singh
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages2504-2509
Number of pages6
ISBN (Electronic)9781728125473
ISBN (Print)9781728125480
DOIs
Publication statusPublished - 1 Dec 2020
Externally publishedYes
Event2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Canberra, Australia
Duration: 1 Dec 20204 Dec 2020

Publication series

Name2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
Country/TerritoryAustralia
CityVirtual, Canberra
Period1/12/204/12/20

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