SOLUTION OF A MULTICRITERIA ASSIGNMENT PROBLEM USING A CATEGORICAL EFFICIENCY CRITERION
DOI:
https://doi.org/10.15588/1607-3274-2024-4-7Keywords:
mathematical and computer modeling of an assignment problem, multicriteria optimization, Pareto set, categorical parameters, logistic curveAbstract
Context. The paper considers a problem of assigning a set of employees to a finite set of operations in a multicriteria statement, under condition of a hierarchical structure of a partial efficiency criterion of performing a set of operations, being presented in such a way that each employee possesses a finite set of competencies and each operation has a finite set of characteristics. Numerical and categorical data types are provided for the use as exogenous parameters of the problem. The relevance of the assignment problem being considered is determined by an extremely wide range of practical applications, both in the classical statements and new modifications, the high demand for which is constantly generated by the dynamically developing economic environment. At the same time, a critically smaller number of scientific publications propose means of modeling and solving multi-criteria assignment problems, despite the importance of this type of problems in decision-making, both in theoretical and practical aspects. In general, in conditions of lack of information, the exogenous parameters of the problem cannot be specified in numerical form, therefore there is a need to use categorical data with further numerical coding.
Objective. The goal of the work is to build a multicriteria mathematical model and, on this basis, carry out a numerical study of the optimization assignment problem, taking into account a hierarchical structure of a partial efficiency criterion of the selection of «operation – employee» pairs.
Method. The study proposes a novel method of solving the assignment problem that implemented as a multi-stage process, which includes the stage of transformation of exogenous parameters of the model, given by categorical variables, based on the implementation of the Pareto principle and logistic mapping, the stage of constructing linear scalarization of the efficiency and the cost criteria.
References
Song M., Cheng L. Solving the reliability-oriented generalized assignment problem by Lagrangian relaxation and Alternating Direction Method of Multipliers, Expert Systems with Applications, 2022, Vol. 205, P. 117644. DOI: 10.1016/j.eswa.2022.117644
Mehlawat M. K., Gupta P., Pedrycz W. A New Possibilistic Optimization Model for Multiple Criteria Assignment Problem, IEEE Transactions on Fuzzy Systems, 2018, Vol. 26, № 4, pp. 1775–1788. DOI: 10.1109/TFUZZ.2017.2751006
Borovicka A. Possible Modifications of the Multiple Criteria Assignment Method, Czech Economic Review, 2013, Vol. 7, pp. 55–67.
Acar E., Aplak H. S. A Model Proposal for a MultiObjective and Multi-Criteria Vehicle Assignment Problem: An Application for a Security Organization, Mathematical and Computational Applications, 2016, Vol. 21(4), P. 39. DOI: 10.3390/mca21040039
Yan Y., Deng Y., Cui S. et al. A policy gradient approach to solving dynamic assignment problem for on-site service delivery, Transportation Research Part E: Logistics and Transportation Review, 2023, Vol. 178, P. 103260 DOI: 10.1016/j.tre.2023.103260
Kondruk N. E. Methods for determining similarity of categorical ordered data, Radio Electronics, Computer Science, Control, 2023, № 2, pp. 31–36. DOI: 10.15588/1607-3274-2023-2-4.
Dahouda M. K., Joe I. A Deep-Learned Embedding Technique for Categorical Features Encoding, IEEE Access, 2021, Vol. 9, pp. 114381–114391. DOI: 10.1109/ACCESS.2021.3104357.
Scikit-learn 1.4.2 [Electronic resource]. Access mode: https://pypi.org/project/scikit-learn/
Dosantos P. S., Bouchet A., Mariñas-Collado I. et al. OPSBC: A method to sort Pareto-optimal sets of solutions in multi-objective problems, Expert Systems With Applications, 2024, Vol. 250, P. 123803. DOI: 10.1016ps://doi.org//j.eswa.2024.123803.
Makarova V.V. Pryntsyp Pareto v konteksti orhanizatsii staloho ahrarnoho zemlekorystuvannia, Pryazovskyi ekonomichnyi visnyk, 2020. Vyp. 1(18), pp. 220–224. DOI: https://doi.org/10.32840/2522-4263/2020-1-39
Route. Schedule. Plan. Assign. Pack. Solve. OR-Tools is fast and portable software for combinatorial optimization [Electronic resource]. Access mode: https://developers.google.com/optimization.
COIN-OR [Electronic resource]. Access mode: https://www.coin-or.org/
SCIP. Solving Constraint Integer Programs. [Electronic resource]. – Access mode: https://www.scipopt.org/
GLPK (GNU Linear Programming Kit) [Electronic resource]. – Access mode: https://www.gnu.org/software/glpk/
Koh R. Princip 80/20 ta 92 fundamental’nih zakoni prirodi. Nauka uspіhu. Kiyv, Vidavnichij centr “KM-BUKS”, 2019, 360 p.
Petrov E. H., Novozhylova M. V., Hrebennik I. V. Metody i zasoby pryiniattia rishen u sotsialno-ekonomichnykh systemakh. Kyiv, Tekhnika, 2003, 240 p.
Blackman I., Chan E. Pareto principle plus statistic methodology in establishing a cost-estimating model, International CIB World Building: 19th Congress, Brisbane, 05–09 May 2013: proceedings. Brisbane, Queensland University of Technology, 2013, pp. 1–14.
Google-Colab [Electronic resource]. Access mode:https://colab.research.google.com/?utm_source=scsindex.
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