Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

November 25, 2024


Pages


DOI

Article

Design of Optimization Algorithms for Supply Chain Allocation of City-Level Public Resource and Case Studies of Practical Applications

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Authors

Feng Hu Affiliation:
Hebei University, Baoding, Hebei, 071000, China.
and Tao Zou Affiliation:
School of Management, Northwestern Polytechnic University, Xi’an, Shaanxi, 710000, China.


Abstract

As an important part of urban public resources, water resources profoundly affect the rationality of urban public resource allocation. In this paper, a multi-objective urban water resource allocation model is proposed by constructing three objective functions of society, economy, and ecology, and setting relevant constraints. Based on the advantages of the simulated annealing algorithm, it is selected as the optimization-solving method. The solving experiments of the algorithm show that the simulated annealing algorithm can jump out of the local optimal many times under the condition of an appropriate temperature drop rate and has good solving performance. Among the four allocation schemes in Jining City, for example, it is found that after the allocation by scheme 4, the average water shortage rate of the city is only 2.63%, and it has taken into account the social, economic and environmental benefits, and it obtains an expert satisfaction score of up to 3.99 points. It shows that the method proposed in this paper can propose an appropriate water allocation scheme with practical application.


Keywords

Simulated annealing algorithm, Multi-objective solution, Public resource allocation, Constraints, 97P10


Citation

Hu, F. & Zou, T. (2024). Design of optimization algorithms for supply chain allocation of city-level public resource and case studies of practical applications. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-3473
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