Optimization Model and Application for Agricultural Machinery Systems Based on Timeliness Losses of Multiple Operations

Author:

Sun Jian12,Zhang Yiming12,Chen Haitao123,Qiao Jinyou12

Affiliation:

1. College of Engineering, Northeast Agricultural University, Harbin 150030, China

2. Heilongjiang Province Technology Innovation Center of Mechanization and Materialization of Major Crops Production, Harbin 150030, China

3. College of Mechanical and Electronic Engineering, East University of Heilongjiang, Harbin 150066, China

Abstract

Present agricultural practices confront issues such as mismatches between tractors and implements, imprecise machinery allocation, and excessive machinery investment. Optimization of agricultural machinery systems was a potent remedy for these concerns. To address inaccuracies in calculating objective functions and the incompleteness of constraints in existing models for agricultural machinery system optimization, a comprehensive mixed integer nonlinear programming (MINP) model for agricultural machinery system optimization was established. The model introduced timeliness loss costs for multiple key operations across various crops into the objective function, and constraints were enhanced by including operation sequence constraints and boundary constraints on initiation and completion dates of those key operations. Taking corn and soybeans as examples, timeliness loss functions of sowing and harvesting operations were derived through experiments. Solving the MINP model by Lingo (V.14.0) software, improvements in total power, workload per unit power, and total operational costs were shown when comparing the optimized machinery system through the MINP model against current systems. When the model omitted considerations for timeliness loss functions and operation sequence constraints, issues arose including an increase in total operational costs and an inversion of operation sequence. The model’s application in devising machinery allocation plans for production units of various operational scales revealed a gradual decrease in total power and costs per unit area with expanding scale, approaching stability when scale exceeded 1600 hm2. This study enriches theory and methodology for optimizing agricultural machinery systems, provides theoretical and technological underpinnings for rational machinery acquisition, and promotes the high-quality progression of comprehensive agricultural mechanization.

Funder

National Key Research and Development Program of China

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

Reference37 articles.

1. Mechanism of factor substitution during rapid development of China’s agricultural mechanization;Pan;Trans. Chin. Soc. Agric. Eng.,2018

2. A systems approach to farm machinery selection;Hunt;Inst. Agric. Eng. J. Proc.,1969

3. Machinery Complement Selection Based on Time Constraints;Hughes;Trans. Asae,1976

4. Methods to Determine Optimum Service Area for Certain Farm Machinery Group and to Select Reasonable Group for Given Service Area;Wan;Trans. Chin. Soc. Agric. Mach.,1984

5. Lu, H., Zhao, Y., Zhou, X., and Wei, Z. (2022). Selection of Agricultural Machinery Based on Improved CRITIC-Entropy Weight and GRA-TOPSIS Method. Processes, 10.

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