Multi-objective optimization for integrated sugarcane cultivation and harvesting planning

被引:7
|
作者
Aliano Filho, Angelo [1 ]
Oliveira, Washington A. [2 ]
Melo, Teresa [3 ]
机构
[1] Univ Tecnol Fed Parana, Dept Matemat, BR-86800020 Apucarana, PR, Brazil
[2] Univ Estadual Campinas, Fac Ciencias Aplicadas, BR-13483531 Limeira, Brazil
[3] Saarland Univ Appl Sci, Business Sch, D-66123 Saarbrucken, Germany
关键词
OR in agriculture; Integrated cultivation and harvesting; planning; Multi-objective optimization; Integer non-linear programming; Sugar-energy industry; SUPPLY CHAIN; DECISION;
D O I
10.1016/j.ejor.2022.12.029
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Sugarcane and its by-products make a relevant contribution to the world economy. In particular, the sugar-energy industry is affected by the timing of sugarcane cultivation and harvesting from which su-crose and bio-energy are produced. We address this issue by proposing a mixed-integer non-linear pro-gramming model to schedule planting and harvesting operations for different varieties of sugarcane. The decisions to be made include the choice of sugarcane varieties to be grown on a given set of plots, the periods for their cultivation, the subsequent harvesting periods, and the type of harvesting equipment. These decisions are subject to various constraints related to matching cultivation periods with harvesting periods according to the maturity cycles of the selected sugarcane varieties, the availability of harvesting machinery, the demand for sucrose and fiber, and further technical requirements. The tactical cultivation and harvesting plans to be determined account for three conflicting objectives, namely maximization of the total sucrose and fiber production, minimization of the total time devoted to harvesting, and mini-mization of the total cost of transporting the harvesting equipment. We develop a tailored exact method based on the augmented Chebyshev scalarization technique extended with a mechanism for identify-ing an initial feasible integer solution that greatly helps reduce the computational effort for obtaining Pareto-optimal solutions. Our computational study with instances that reflect the current cultivation and harvesting practices in Brazil demonstrate the effectiveness of the proposed methodology. In addition, a comparative analysis reveals the trade-offs achieved by alternative planting and harvesting schedules, thereby facilitating the decision-making process. (c) 2022 Elsevier B.V. All rights reserved.
引用
收藏
页码:330 / 344
页数:15
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