【摘要】 为解决生鲜待加工农产品运输中，因采用闭合式运输导致运输车辆在卸料线处长时间排队等待卸货的问题，提出一种考虑单位运输成本分段计费的半开放式运输车辆调度优化模型。提出一种基于降维策略的混合遗传模拟退火算法(HGSA-DR)。利用可行解全域遍历策略将多层要素整合为系列运输单元组，用自然数编码表示调度方案以实现降维，降低问题的求解难度。在降维后的解空间内，融合自适应变异算子与动态降温策略进行高效搜索，利用基于高斯分布排队倒推机制，生成最终调度优化方案。结果表明，所提算法生成的方案能显著提高车辆利用率。同时，相较于基于降维策略的遗传算法和模拟退火算法，成本可优化14.23%、17.40%。对农产品加工企业具有显著的实际应用价值和意义。更多还原

【Abstract】 To address the traffic congestion at the discharge lines due to closed-loop transportation in the distribution of fresh agricultural products for processing, this paper proposes a semi-open vehicle scheduling optimization model that incorporates segmented transportation cost pricing. A dimensionality reduction-based hybrid genetic simulated annealing algorithm(HGSA-DR) is introduced. By adopting a global traversal strategy for feasible solutions, multi-layer elements are integrated into a series of transport unit groups. The scheduling scheme is encoded using natural numbers to achieve dimensionality reduction, thereby lowering the complexity of the problem. Within the reduced solution space, an adaptive mutation operator and a dynamic cooling strategy are incorporated for efficient search. Finally, a Gaussian distribution-based backward queuing mechanism is applied to generate the optimized scheduling scheme. Results demonstrate the proposed algorithm markedly improves vehicle utilization. Compared to the dimensionality reduction-based genetic algorithm and simulated annealing algorithm, it reduces costs by 14.23% and 17.40% respectively. Thus, it has great potentials for enterprises specialized in agricultural product processing.更多还原