Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Jiang, Yiping; Bian, Bei

doi:10.3390/agronomy9110724

Cited by 4 publications

(2 citation statements)

References 37 publications

(52 reference statements)

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“…The design baseline is a multi-objective optimal design, an area of mathematical optimization involving more than one objective function to be optimized simultaneously. The genetic algorithm (GA), as a highly popular evolutionary algorithm having well-tried records in agricultural engineering [29][30][31][32], is employed and hybridized with a goal attainment method in the synthesis of the first mechanism, whereas a quasi-Newton optimization method (QNM) is used for the second mechanism synthesis. The results from both optimal design methods are compared with each other and with those of other studies, and then the two mechanisms are simulated statically and dynamically to verify the results.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Design and Development of a Four-Bar Mechanism for Weed Control

et al. 2022

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Weeds compete with crops for water, nutrients, and light consequently, have adverse effects on the crop yield and overall productivity. Mechanical weeding is the most common non-chemical method for weed control, which is applied in organic farming, and the weed cultivator is the most common implement in mechanical weeding. This study aimed to design and develop an innovative active tool to optimize the cultivation depth, which can avoid damage to crop roots and improve the key performance indicators of an inter-row cultivator. A quasi-Newton optimization method and a hybrid of the non-dominated sorting genetic algorithm (NSGA-II) and goal attainment method were separately applied to synthesize and develop a four-bar mechanism for weeding requirements. The transmission angle of the mechanism and the desired path of the weeding blade were simultaneously optimized using these multi-objective optimization techniques. The performance of the developed four-bar cultivator based on the optimization techniques was compared with the ones developed based on the classic methods and also with several conventional tools evaluated in other studies. The results showed that applying the quasi-Newton optimization method and hybrid genetic algorithm can propose a more effective weed cultivator in terms of performance indicators, namely weeding performance, mechanical damage to crop plants and cultivation depth. In addition, the optimization of the transmission angle guaranteed the smooth rotations in the mechanism’s joints.

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Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Design and Development of a Four-Bar Mechanism for Weed Control

et al. 2022

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“…(3) A mixed genetic algorithm (MGA) is proposed to solve the joint optimization model, for which purpose MGA has better performance and efficiency than other solvers. The most relevant literature concerns the cold-chain logistics of fresh agriproduct [2], the path optimization of MTJD [3], the splitting and merging of orders [4], and warehousing and distribution integration [5,6]. In general, prior studies have looked at the actual influencing variables of the distribution process from various angles, to reduce the time requirements and cost of the e-commerce distribution process.…”

Section: Introductionmentioning

confidence: 99%

Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail

Zhan

Jiang

2022

Sustainability

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Community retail is an important research issue in the field of fresh agriproduct e-commerce. This paper focuses on the problem of last-mile multi-temperature joint distribution (MTJD), which combines time coupling, order allocation, and vehicle scheduling. Firstly, according to the temperature of a refrigerated truck in multi-temperature zones, a split-order packing decision is proposed to integrate the different types of fresh agriproduct. Then, the order allocation strategy is incorporated into a comprehensive picking and distribution schedule, while taking into account the time-coupling of picking, distribution, and delivery time limit. To improve consumer satisfaction and reduce order fulfillment costs, an optimization model combining multi-item order allocation and vehicle scheduling is established, to determine the optimal order allocation scheme and distribution route. Finally, taking fresh agriproduct community retail in the Gulou District of Nanjing as an example, the effectiveness and feasibility of the model are illustrated. The numerical results of medium- to large-scale examples show that, compared with the variable neighborhood search algorithm (VNS) and genetic algorithm (GA), the mixed genetic algorithm (MGA) can save 29% of CPU time and 65% of iterations. This study considers the integrated optimization of multiple links, to provide scientific decision support for fresh agriproduct e-commerce enterprises.

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Multi-objective integrated harvest and distribution scheduling for fresh agricultural products with farm-to-door requirements using Q-learning and problem knowledge-based cooperative evolutionary algorithms

Ma,

Pu,

2025

Computers & Industrial Engineering

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Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Cited by 4 publications

References 37 publications

Multi-Objective Optimal Design and Development of a Four-Bar Mechanism for Weed Control

Multi-Objective Optimal Design and Development of a Four-Bar Mechanism for Weed Control

Integrated Optimization of Order Allocation and Last-Mile Multi-Temperature Joint Distribution for Fresh Agriproduct Community Retail

Multi-objective integrated harvest and distribution scheduling for fresh agricultural products with farm-to-door requirements using Q-learning and problem knowledge-based cooperative evolutionary algorithms

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