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

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Bibliographic Details
Title:	Crowdsource-enabled integrated production and transportation scheduling for smart city logistics.
Authors:	Feng, Xin¹ (AUTHOR), Chu, Feng^2,3 (AUTHOR) feng.chu@univ-evry.fr, Chu, Chengbin⁴ (AUTHOR), Huang, Yufei⁵ (AUTHOR)
Source:	International Journal of Production Research. Apr2021, Vol. 59 Issue 7, p2157-2176. 20p. 1 Black and White Photograph, 4 Diagrams, 7 Charts, 2 Graphs.
Subjects:	Production scheduling, Transportation schedules, Problem solving, Smart cities, Genetic algorithms, 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. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
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. [ABSTRACT FROM AUTHOR]
ISSN:	00207543
DOI:	10.1080/00207543.2020.1808258