Development of a Heuristic Method for Solving the Problem of Optimizing a Feed Mixture Production Plan with Fuzzy Constraints

The compilation of optimal production plans often requires consideration of the fuzziness in certain initial information. Therefore, a pertinent issue in the theory and practice is the solution of production plan optimization problems under conditions of fuzzy information using mathematical models and tools of fuzzy sets. The research aims to develop various formulations for optimization problems of production plans using the example of a feed production plan. The problem is addressed based on a modified model considering fuzzy constraints by adapting various optimality principles. The research focuses on the processes of feed mixture production at the Makinsk poultry farm, characterized by fuzzy constraints on feed composition. New formulations of optimization problems under fuzzy constraints are obtained in the form of fuzzy mathematical programming problems, and heuristic methods for their solution are proposed. Various scenarios are considered, where the original multi-criteria optimization problem can be reduced to a single-criterion problem. For each formulation of the optimization problem, modifications of Pareto optimality methods and the main criterion are applied, ensuring the effective utilization of expert information and the decision maker’s knowledge during the optimization process and the selection of the best solution.

Authors

Institutions

Publication Details

Journal
Symmetry
Published
2026-06-30
DOI
https://doi.org/10.3390/sym18071121
Primary Topic
Optimization and Mathematical Programming
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a Heuristic Method for Solving the Problem of Optimizing a Feed Mixture Production Plan with Fuzzy Constraints

Timur Toleuov, Zhumazhan Kulmagambetova, Batyr Orazbayеv, Raigul Tuleuova et al.
Symmetry
Optimization and Mathematical Programming
article

Development of a Heuristic Method for Solving the Problem of Optimizing a Feed Mixture Production Plan with Fuzzy Constraints

Timur Toleuov, Zhumazhan Kulmagambetova, Batyr Orazbayеv, Raigul Tuleuova, Yerbol Ospanov, Valentina Makhatova, Balbupe Utenova
article en

Abstract

The compilation of optimal production plans often requires consideration of the fuzziness in certain initial information. Therefore, a pertinent issue in the theory and practice is the solution of production plan optimization problems under conditions of fuzzy information using mathematical models and tools of fuzzy sets. The research aims to develop various formulations for optimization problems of production plans using the example of a feed production plan. The problem is addressed based on a modified model considering fuzzy constraints by adapting various optimality principles. The research focuses on the processes of feed mixture production at the Makinsk poultry farm, characterized by fuzzy constraints on feed composition. New formulations of optimization problems under fuzzy constraints are obtained in the form of fuzzy mathematical programming problems, and heuristic methods for their solution are proposed. Various scenarios are considered, where the original multi-criteria optimization problem can be reduced to a single-criterion problem. For each formulation of the optimization problem, modifications of Pareto optimality methods and the main criterion are applied, ensuring the effective utilization of expert information and the decision maker’s knowledge during the optimization process and the selection of the best solution.

SymmetryVol. 18(7)
L. N. Gumilyov Eurasian National University (KZ), Aktobe Regional State University named after K.Zhubanov (KZ), Atyrau University of Oil and Gas (KZ), Khalel Dosmukhamedov Atyrau University (KZ), Shakarim University (KZ)
Openalex Percentile: Top 8%
Optimization and Mathematical Programming
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.