Centralized bundle generation in auction-based collaborative transportation

Area of Science:

• Operations Research
• Logistics Management
• Computational Economics

Background:

• Horizontal collaborations in logistics involve carriers jointly performing operations to enhance efficiency and sustainability.
• Combinatorial auctions are used to organize the exchange of transportation requests among carriers.
• The exponential growth in the number of possible bundles makes offering all combinations computationally intractable for real-world applications.

Purpose of the Study:

• To develop an efficient method for reducing the set of bundles in combinatorial auctions for logistics.
• To address the Bundle Generation Problem (BuGP) by maximizing total coalition profit while ensuring feasible bundle assignments.
• To overcome the challenge of evaluating the objective function with incomplete information.

Main Methods:

• Definition of the Bundle Generation Problem (BuGP).
• Development of a proxy for the objective function to assess bundle attractiveness under incomplete information.
• Implementation of a genetic algorithms-based framework to generate feasible and attractive bundles.

Main Results:

• An efficient reduction of the complete set of bundles to a manageable subset.
• Achievement of very good solution quality in bundle generation.
• Significant reduction in the computational time for the auction procedure.

Conclusions:

• The proposed approach makes combinatorial auctions of real-world size computationally tractable.
• The method effectively balances maximizing coalition profit with ensuring feasible assignments.
• This work represents a significant advancement for applying combinatorial auctions in practical logistics settings.