Abstract
This paper constructed a biobjective model based on the total cost and time satisfaction to provide a desirable solution to the distribution and inventory cooperation of agricultural means supply chain. The model simulated how the distribution center and retailers collaborate to meet the needs of the order customer in the random lead time and out-of-stock loss costs. By the features of the model, the biobjective genetic algorithm was improved based on elitism selection, aiming to improve the quality of noninferior solution in biobjective model. Finally, the influence degree of the lead time of delivery, unit inventory cost, and unit transport cost on the total cost of the system was quantified through the analysis of examples and sensitivity of model parameters. This research has provided valuable new insights into the distribution and inventory coordination of supply chain.
Highlights
Grain is a strategic material essential to the survival and development of our society
Agricultural production materials like pesticides and fertilizers guarantee the sustainable development of agriculture and maintain the stability of the rural market and boost farmers’ income
The efficiency and cost of agricultural means supply directly determine whether the agricultural production system could operate highly efficiently
Summary
Grain is a strategic material essential to the survival and development of our society. Lee and Sook [4] established a multiperiod linear programming model and studied the production-distribution coordination of the supply chain through simulation of random factors such as machine capacity and transport capacity with optimization methods; Torabi and Hassini [5] established a multiobjective mathematical programming model with probability constraints based on a fuzzy solution algorithm to study the supply and demand planning of the supply chain composed of multiple suppliers, a single manufacturer, and multidistribution centers, while Tian et al [6] constructed a multiperiod bilevel stochastic programming model, proposing a simulation-optimization solution to deal with compensation problems. Drawing on the optimal design of distribution network and inventory control, Yan [8] constructed a dual-objective inventory joint control model for multilevel distribution network supply chain, which fully considers the interaction and mutual influence between the joints
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