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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Solving The Winner Determination Problem For Online B2b Transportation Matching Platforms, Hoong Chuin Lau, Baoxiang Li
Solving The Winner Determination Problem For Online B2b Transportation Matching Platforms, Hoong Chuin Lau, Baoxiang Li
Research Collection School Of Computing and Information Systems
We consider the problem of matching multiple shippers and transporters participating in an online B2B last-mile logistics platform in an emerging market. Each shipper places a bid that is made up of multiple jobs, where each job comprises key information like the weight, volume, pickup and delivery locations, and time windows. Each transporter specifies its vehicle capacity, available time periods, and a cost structure. We formulate the mathematical model and provide a Branch-and-Cut approach to solve small-scale problem instances exactly and larger scale instances heuristically using an Adaptive Large Neighbourhood Search approach. To increase the win percentage of both shippers …
Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau
Combinatorial Auction For Transportation Matching Service: Formulation And Adaptive Large Neighborhood Search Heuristic, Baoxiang Li, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
This paper considers the problem of matching multiple shippers and multi-transporters for pickups and drop-offs, where the goal is to select a subset of group jobs (shipper bids) that maximizes profit. This is the underlying winner determination problem in an online auction-based vehicle sharing platform that matches transportation demand and supply, particularly in a B2B last-mile setting. Each shipper bid contains multiple jobs, and each job has a weight, volume, pickup location, delivery location and time window. On the other hand, each transporter bid specifies the vehicle capacity, available time periods, and a cost structure. This double-sided auction will be …
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Research Collection School Of Computing and Information Systems
Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …