An Improved Tabu search algorithm for the multi-period bid generation problem with the consideration of delivery lead times

Jelodari, Elham, Haoxun, Chen, Prins, Christian and Demir, Emrah ORCID: https://orcid.org/0000-0002-4726-2556 2019. An Improved Tabu search algorithm for the multi-period bid generation problem with the consideration of delivery lead times. Presented at: 9th IFAC Conference on Manufacturing Modelling, Management and Control, Berlin, Germany, 28-30 August 2019. IFAC-PapersOnLine. , vol.52 (13) Elsevier, pp. 2602-2607. 10.1016/j.ifacol.2019.11.599

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Abstract

In addition to standard delivery costs, shippers are concerned with delivery lead times. Shorter delivery lead times provide better service to customers. This paper investigates the bid generation problem of a carrier in collaborative transportation realized via a combinatorial auction. In this paper, we propose a multi-period bid generation problem with two types of pickup and delivery requests, namely reserved and selective requests. This problem is an extension of pickup and delivery problem with time windows. This problem arises when a shipper applies an auction for the procurement of transportation services from carriers. In each period, the carrier may have reserved requests that must be served by itself. This carrier wants to determine within a time horizon of multi periods which requests to bid and serve among a set of selective requests open for bid and its multi-period routing plan to maximize its profit and minimize delivery lead times. This problem is NP-hard. We propose an Improved Tabu Search (ITS) algorithm to solve it. The algorithm is evaluated on instances with 20 to 100 requests. The computational results show that the proposed algorithm significantly outperforms CPLEX with much shorter computation times.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Business (Including Economics)
Publisher:	Elsevier
ISSN:	2405-8963
Related URLs:	Organisation
Last Modified:	13 May 2026 08:54
URI:	https://orca.cardiff.ac.uk/id/eprint/127479

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