Aiming at the problems of high loss and low satisfaction rates in the distribution process, this paper studies the distribution optimization of community group buying. Considering customer satisfaction, this paper studies the fixed cost of vehicles, the variable cost during transportation, the penalty cost for exceeding the time, the cost of goods damage during transportation, and the cost of self-pickup service in the process of distribution optimization. It constructs the optimization model of community group purchase fresh food logistics distribution considering customer satisfaction with the goal of minimizing the total distribution cost. According to the model, the genetic algorithm is used to solve it, and a numerical example is used to verify the conclusion. The optimization model of fresh food distribution in community group purchase considering customer satisfaction proposed in this paper is representative. This study can provide some theoretical reference for the planning of community group purchase distribution schemes.
In the current climate of traffic congestion and frequent traffic accidents due to increasing pressure on transport, the birth and development of driverless cars is particularly important. However, as the technologies of unmanned vehicles are not yet perfect, it becomes more practical to carry goods at low speed - unmanned delivery - than to carry people at high speed. In order to achieve the goal of making full use of the existing road resources and improving the efficiency of distribution in logistics, this paper uses an intelligent algorithm - the Pelican algorithm - to optimise the cost of the unmanned vehicle and solve for its minimum cost.
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