Asset Details
Do you wish to reserve the book?
A hybrid metaheuristic algorithm for collaborative scheduling optimization of port coal transportation
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A hybrid metaheuristic algorithm for collaborative scheduling optimization of port coal transportation
Do you wish to request the book?
A hybrid metaheuristic algorithm for collaborative scheduling optimization of port coal transportation
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
A hybrid metaheuristic algorithm for collaborative scheduling optimization of port coal transportation
2025
Overview
Port coal transportation scheduling faces significant challenges with slow response times and low efficiency, especially under dynamic disruptions. To address these issues, this research proposes a novel hybrid meta-heuristic algorithm that deeply integrates the improved Ant Colony Optimization (IACO) and the Greedy Randomized Adaptive Search Procedure (GRASP). The proposed IACO-GRASP algorithm is designed to enhance collaborative scheduling by effectively coordinating global exploration and local optimization. The major findings from a case study at Qinhuangdao Port demonstrate that the algorithm increases ship turnover efficiency by 36.25% and reduces the empty running rate by 25.18%, leading to an estimated annual cost saving of 18.95 million yuan. Comparative experiments also show that the algorithm’s convergence speed is significantly improved over other hybrid methods. These findings highlight the potential of IACO-GRASP as a robust and efficient decision-support tool for building responsive, resource-optimized, and intelligent port operations.
