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

Jian Sun, Yiming Zhang, Haitao Chen () and Jinyou Qiao ()
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Jian Sun: College of Engineering, Northeast Agricultural University, Harbin 150030, China
Yiming Zhang: College of Engineering, Northeast Agricultural University, Harbin 150030, China
Haitao Chen: College of Engineering, Northeast Agricultural University, Harbin 150030, China
Jinyou Qiao: College of Engineering, Northeast Agricultural University, Harbin 150030, China

Agriculture, 2023, vol. 13, issue 10, 1-19

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 hm 2 . 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.

Keywords: agricultural machinery system; mixed integer nonlinear programming (MINP); timeliness loss; operation sequence; operating scale (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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