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Crowdsource-enabled integrated production and transportation scheduling for smart city logistics

Abstract : With city logistics becoming more and more important, increasing attention has been paid to the ‘last-mile delivery’ in urban areas. We investigate a novel crowdsource-enabled integrated production and transportation scheduling problem in the paper. The problem is first formulated into a mixed-integer linear program and its strong NP-hardness is proved. To better understand this complex problem, two sub-problems: a production and transportation scheduling problem and a crowdsourced bid selection problem are analysed. Based on problem properties, a Genetic Algorithm (GA) and a lower bound (LB) are developed to solve the original problem. Experimental results with up to 100 customers show that the GA outperforms the well-known commercial MIP solver CPLEX. Especially, (1) the GA can yield near-optimal solutions for all the tested instances with an average gap of 10.17% from the lower bound, while CPLEX provides feasible solutions only for instances with no more than 30 customers; (2) the average computation time of the GA is only 0.93% of that required by CPLEX; Besides, sensitivity analysis demonstrates advantages of introducing crowdsourced delivery into city logistics.
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https://hal.archives-ouvertes.fr/hal-02936966
Contributor : Frédéric Davesne <>
Submitted on : Friday, September 11, 2020 - 11:10:33 PM
Last modification on : Saturday, September 12, 2020 - 3:29:29 AM

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Xin Feng, Feng Chu, Chengbin Chu, Yufei Huang. Crowdsource-enabled integrated production and transportation scheduling for smart city logistics. International Journal of Production Research, Taylor & Francis, In press, pp.1-20. ⟨10.1080/00207543.2020.1808258⟩. ⟨hal-02936966⟩

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