Ant Colony Optimization Algorithm for Workforce Planning

Abstract

Abstract-The workforce planning helps organizations to optimize the production process with aim to minimize the assigning costs. A workforce planning problem is very complex and needs special algorithms to be solved. The problem is to select set of employers from a set of available workers and to assign this staff to the jobs to be performed. Each job requires a time to be completed. For efficiency, a worker must performs a minimum number of hours of any assigned job. There is a maximum number of jobs that can be assigned and a maximum number of workers that can be assigned. There is a set of jobs that shows the jobs on which the worker is qualified. The objective is to minimize the costs associated to the human resources needed to fulfill the work requirements. On this work we propose a variant of Ant Colony Optimization (ACO) algorithm to solve workforce optimization problem. The algorithm is tested on a set of 20 test problems. Achieved solutions are compared with other methods, as scatter search and genetic algorithm. Obtained results show that ACO algorithm performs better than other two algorithms.

Hybrid Ant Colony Optimization Algorithm for Workforce Planning

“…The set of test problems consists of 20 used in [1], [8]. In our previous work [8] we show that our ACO algorithm outperforms the genetic and scatter search algorithms from [1]. The number of iterations is fixed to be maximum 100.…”

“…In this section we will apply the ACO algorithm for workforce planing from our previous work [8], which is without local search procedure. One of the main points of the ant algorithm is the proper representation of the problem by graph.…”

“…So far the Ant Colony Optimization (ACO) algorithm is proved to be very effective solving various complex optimization problems [7], [10]. In our previous work [8] we propose ACO algorithm for workforce planning. We have considered the variant of the workforce planning problem proposed in [1].…”

“…We have considered the variant of the workforce planning problem proposed in [1]. Current paper is the continuation of [8]. We propose a hybrid ACO algorithm which is a combination of ACO with a local search procedure.…”

Ant Colony Optimization Algorithm for Workforce Planning: Influence of the Evaporation Parameter

“…Ant Colony Optimization (ACO) algorithm is proved to be very effective solving various complex optimization problems [7], [11]. In our previous work [8], [9] we propose ACO algorithm for workforce planning. We have considered the variant of the workforce planning problem proposed in [1].…”