An Improved “Walk on Equations” Monte Carlo Algorithm for Linear Algebraic Systems

Todorov, Venelin; Ikonomov, Nikolay; Apostolov, Stoyan; Dimov, Ivan; Georgieva, Rayna; Dimitrov, Yuri

doi:10.1007/978-3-030-22723-4_14

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…Other authors include uncertainty, [12,14,15,22,23]. Statistical approaches for similar problems are applied in [19][20][21]. Most of the authors simplify the problem by omitting some of the constraints.…”

Section: Introductionmentioning

confidence: 99%

New Local Search Procedure for Workforce Planning Problem

Fidanova

Luque

2020

Cybernetics and Information Technologies

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Optimization of workforce planning is important for any production area. This leads to an improvement in production process. The aim is minimization of the assignment costs of the workers, who will do the jobs. The problem is to select and assign employers to the jobs to be performed. The constraints are very strong, coming both from the specifics of the production process and from the legislation. Sometimes it is difficult to find feasible solutions. The complexity of the problem is very high and the needed number of calculations is exponential, therefore only specially developed algorithms can be applied. The objective is to minimize the assignment cost, while respecting all requirements. We propose a new hybrid metaheuristic algorithm to solve the workforce-planning problem, which is a combination between Ant Colony Optimization (ACO) and suitable local search procedure.

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