| Title |
Crowdsource-enabled integrated production and transportation scheduling for smart city logistics |
| ID_Doc |
40815 |
| Authors |
Feng, X; Chu, F; Chu, CB; Huang, YF |
| Title |
Crowdsource-enabled integrated production and transportation scheduling for smart city logistics |
| Year |
2021 |
| Published |
International Journal Of Production Research, 59, 7 |
| DOI |
10.1080/00207543.2020.1808258 |
| 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. |
| Author Keywords |
Crowdsourced delivery; last-mile delivery; job scheduling; city logistics; genetic algorithm |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000565028000001 |
| WoS Category |
Engineering, Industrial; Engineering, Manufacturing; Operations Research & Management Science |
| Research Area |
Engineering; Operations Research & Management Science |
| PDF |
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