InterCriteria Analysis of Different Hybrid Ant Colony Optimization Algorithms for Workforce Planning View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019-06-22

AUTHORS

Stefka Fidanova , Olympia Roeva , Gabriel Luque , Marcin Paprzycki

ABSTRACT

Every organization Fidanova, Stefka factory optimize their production process with a help of workforce planing. The aim is minimization of the assignment costs of the workers, who will do the jobs. The problem is very Roeva, Olympia and needs exponential number of calculations, therefore special algorithms are developed to be solved. The problem is to select employers and to assign them to the jobs to be performed. This problem has very strong constraints and it is difficult to find feasible solutions. The objective is to fulfil the requirements and to Luque, Gabriel the assignment cost. We propose a hybrid Ant Colony Optimization (ACO) algorithm to solve the workforce problem, which is a combination between ACO and an appropriate local search procedure. In Paprzycki, Marcin investigation InterCriteria Analysis (ICrA) is applied over numerical results obtained from ACO algorithms with the suggested different variants of local search procedures. Based on ICrA the ACO hybrid algorithms performance is examined and compared. More... »

PAGES

61-81

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-22723-4_5

DOI

http://dx.doi.org/10.1007/978-3-030-22723-4_5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1117402913


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