Optimization and public transport tendering: a case study in Southern Italy

Area of Science:

• Operations Research
• Transportation Science
• Heuristic Algorithms

Background:

• Public transport organization faces challenges in designing optimal lots.
• Balancing cost and service level is crucial for efficient public transport operations.
• Existing models may not fully address real-world complexities of lot design.

Purpose of the Study:

• To develop and present a multi-start heuristic approach for optimal lot design in public transport.
• To model the lot design problem as a graph partitioning problem.
• To incorporate cost and service level considerations into the optimization process.

Main Methods:

• A multi-start heuristic algorithm is employed.
• Adaptive Large Neighborhood Search (ALNS) is utilized for solution optimization.
• The problem is modeled as a graph partitioning problem.

Main Results:

• The proposed algorithm identifies high-quality solutions for the public transport lot design problem.
• Computational study results based on real data from Southern Italy are presented.
• The approach effectively balances cost and service level objectives.

Conclusions:

• The multi-start heuristic algorithm offers an effective method for optimizing public transport lot design.
• The approach is applicable to real-world scenarios within the Italian transport system.
• This research contributes to improving the efficiency and service quality of public transport organizations.