A population algorithm based on randomized tabu thresholding for the multi-commodity pickup-and-delivery traveling salesman problem

作者：Lu, Yongliang; Benlic, Una; Wu, Qinghua^*

来源：Computers & Operations Research, 2019, 101: 285-297.

DOI：10.1016/j.cor.2018.08.006

• Heuristics
• Traveling salesman problem
• Pickup and delivery
• Tabu thresholding

The multi-commodity pickup-and-delivery traveling salesman problem (m-PDTSP) is a variant of the classic traveling salesman problem with pickup and delivery. It arises from a number of real-life applications where a capacitated vehicle services a set of customers that provide or require certain amounts of different commodities. In this paper, we present a simple but highly effective population based algorithm for m-PDTSP (denoted as PRTTA) that uses a randomized tabu thresholding algorithm for local improvement. Extensive experiments on a large set of benchmark instances show that the proposed approach competes very favorably with the existing methods from the literature.

• 出版日期2019-1
• 单位华中科技大学