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Actual Problems
of Economics and Law

 

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DOI: 10.21202/1993-047X.14.2020.1.1.174-185

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Authors :
1. Irina Yu. Poliakova, post-graduate student
Saint-Petersburg State University



A variable neighborhood descent heuristic for a multi-item lot-sizing problem with remanufacturing


Objective: to implement the neighborhood descent heuristic approach into solving the lot-sizing problem.


Methods: a variable neighborhood descent heuristic approach and a framework of lot-sizing problem.


Results: dynamic lot-sizing problem is supposed to be an NP-hard problem – a problem for which there is no known polynomial algorithm, so the time to find a solution grows with a problem size. In the article, we explain the  basic lot-sizing, lotsizing in closed-loop, describe methods used by other researchers, and provide reasoning for using a variable neighborhood descent heuristic method. Implementation of the method is presented in a numerical example. Application of the method significantly reduces estimation time when searching for lot-sizing problem solution. Application of the method significantly reduces estimation time when searching for lot-sizing problem solution.


Scientific novelty: the method may significantly reduce time expenses during the solution of the lot-sizing problem.


Practical significance: the method may be implemented for solving the lot-sizing problem in various industries, such as pulp and paper, consumer goods industry and heavy industry.


Keywords :

neighborhood descent; lot-sizing problem; remanufacturing; multi-item lot-sizing; heuristic approach; closed-loop; reverse logistics


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Citation :

Poliakova I. Yu. A variable neighborhood descent heuristic for a multi-item lot-sizing problem with remanufacturing, Actual Problems of Economics and Law, 2020, Vol. 14, No. 1, pp. 174–185 (in Engl.). DOI: http://dx.doi.org/10.21202/1993-047X.14.2020.1.1.174-185.


Type of article : The scientific article

Date of receipt of the article :
10.06.2019

Date of adoption of the print :
10.01.2020

Date of online accommodation :
25.03.2020