Crowdsource-enabled integrated production and transportation scheduling for smart city logistics. Issue 7 (3rd April 2021)

• Record Type: Journal Article
• Authors: Feng, Xin; Chu, Feng; Chu, Chengbin; Huang, Yufei
• Is Part Of: International journal of production research. Volume 59:Issue 7(2021)
• Page Start: 2157
• Page End: 2176
• Publication Date: 2021-04-03
• Subjects: Crowdsourced delivery -- last-mile delivery -- job scheduling -- city logistics -- genetic algorithm; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2020.1808258
• Languages: English
• ISSNs: 0020-7543

Abstract

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.