关键词: 众包物流, 即时配送, 收益激励, 客户满意度, 粒子群算法

Abstract: Based on the characteristics of customer requirements for instant delivery that are not entirely rigid, and of participants’ enthusiasm that is not high in the crowdsourcing logistics distribution mode, this paper introduces the fuzzy time window, and quantifies the customer satisfaction rate into the fuzzy function of time that the crowdsourcing logistic personnel arrives at purchaser location. Under the premise of ensuring a certain customer satisfaction, the research on logistics scheduling based on instant distribution and revenue incentives model is constructed in order to maximize the crowdsourcing logistics personnel’s earnings considering the opportunity, overtime, overload punishment cost.Then this paper uses particle swarm optimization (PSO) algorithm with the dynamic weight to solve the proposed problems, and through the example analysis, the results show that the model is feasible and effective in keeping balance between customer and crowdsourcing logistics personnel.

Key words: crowdsourcing logistics, instant distribution, revenue incentive, customer’s satisfaction, particle swarm optimization