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Research on Multi-Cooperative Combine-Integrated Scheduling Based on Improved NSGA-II Algorithm

Author

Listed:
  • Li Ma

    (College of Engineering, Northeast Agricultural University, Harbin, China)

  • Yidi Wang

    (College of Engineering, Northeast Agricultural University, Harbin, China)

  • Meiqiong Ma

    (JI Baiwang Technology Co., Ltd., Shenzhen, China)

  • Jiyun Bai

    (College of Arts and Sciences, Northeast Agricultural University, Harbin, China)

Abstract

To promote the integration and optimal allocation of agricultural machinery resources to achieve the purpose of reducing cost and increasing efficiency, the scheduling problem of agricultural machinery in agricultural machinery cooperatives based on the trans-regional operation mode was studied in this paper, Considering multiple agricultural machinery points, multiple types, operation time windows, space distance and other factors, the multi-objective programming mathematical model with the lowest total cost of deployment, the highest service punctuality and the least use of harvester was established by applying path optimization and theory of job shop scheduling. NSGA-II was used to solve the model in this paper. According to the model features, this paper designed chromosome coding and the process of emergence, crossover and variation of initial population. Combined with the actual situation of rice harvesting in Wuchang City, the above scheduling theory was applied. The experimental results showed the validity and feasibility of the scheduling model and the algorithm.

Suggested Citation

  • Li Ma & Yidi Wang & Meiqiong Ma & Jiyun Bai, 2021. "Research on Multi-Cooperative Combine-Integrated Scheduling Based on Improved NSGA-II Algorithm," International Journal of Agricultural and Environmental Information Systems (IJAEIS), IGI Global, vol. 12(4), pages 1-21, October.
    • Handle: RePEc:igg:jaeis0:v:12:y:2021:i:4:p:1-21
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    References listed on IDEAS

    as
    1. Pilla, Venkata L. & Rosenberger, Jay M. & Chen, Victoria & Engsuwan, Narakorn & Siddappa, Sheela, 2012. "A multivariate adaptive regression splines cutting plane approach for solving a two-stage stochastic programming fleet assignment model," European Journal of Operational Research, Elsevier, vol. 216(1), pages 162-171.
    2. Dariush Khezrimotlagh & Yao Chen, 2018. "The Optimization Approach," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 107-134, Springer.
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    Cited by:

    1. Li Ma & Minghan Xin & Yi-Jia Wang & Yanjiao Zhang, 2022. "Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services," Mathematics, MDPI, vol. 10(21), pages 1-22, October.

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