Assignment constraints in shared transportation services

Area of Science:

• Operations Research
• Logistics Management
• Supply Chain Optimization

Background:

• The logistics sector faces challenges from competitive markets, rising fuel costs, and underutilized fleets.
• Increasing pressure for economic and ecological efficiency drives demand for solutions that leverage idle capacities.
• The Sharing Economy facilitates collaborative usage through platforms for exchanging goods and services.

Purpose of the Study:

• To quantify the potential cost savings of horizontal collaborations in a centralized logistics framework.
• To analyze the impact of constraints on collaborative gains, particularly concerning customer distribution.
• To investigate the effectiveness of collaborative frameworks for carriers with multiple vehicles.

Main Methods:

• Development of an Adaptive Large Neighborhood Search algorithm to solve the collaborative pickup and delivery problem.
• Computational study using test instances to evaluate the proposed framework.
• Inclusion of constraints to ensure acceptable solutions for all participating carriers.

Main Results:

• Confirmed cost savings of 20-30%, with greater potential in areas of high regional customer overlap.
• Identified uneven customer distribution as a significant barrier to collaboration.
• Demonstrated that constraints reduce collaborative gains in single-vehicle scenarios but not in multi-vehicle settings.

Conclusions:

• Centralized collaborative frameworks offer substantial cost savings in logistics.
• These frameworks can mitigate customer and profit share losses, allowing carriers to retain key customers.
• Horizontal collaboration is a viable strategy for improving economic and ecological efficiency in the logistics sector.