Advances in Fuzzy Optimization for Transportation Planning Under Uncertainty

Dear Colleagues,

Transportation planning plays a key role in establishing and operating an efficient transportation system that can better serve and benefit the human life and sustainable development of all the industries.

This type of planning is advanced work that should be carried out before the optimization plans are applied in the real world. In this case, it is difficult for transportation planners to accurately capture or predict the real-time state of the transportation system at the time when the plans are implemented, since the system state is constantly changing. The parameters of the transportation system related to the demand, time, speed, capacity, carbon emissions, etc., are thereby uncertain in the planning stage. As a result, transportation planning should be resolved under uncertainty to enhance its feasibility, especially reliability, when being applied in the real world.

Fuzzy set theory and fuzzy numbers have been well employed to model the uncertainty in the process system engineering, especially in the cases where there are not enough historical data available to model the uncertainty. Based on the use of fuzzy numbers, fuzzy optimization models can be constructed to address the optimization problems under uncertainty, in which fuzzy parameters can result in variable fuzziness. The results of the fuzzy optimization can provide solid decision support for the transportation planners to optimize and utilize the transportation system to better serve its users.

This Special Issue will contribute to the adoption of fuzzy optimization in the all kinds of transportation planning problems under uncertainty. The transportation planning can be strategic, tactical and operational. Green transportation planning is especially relevant to this Special Issue. The (multi-source) uncertainty of the transportation system is encouraged to be modeled by fuzzy numbers. Besides the traditional concepts of fuzzy numbers (e.g., interval, triangular, and trapezoidal fuzzy number), we especially welcome the design and use of novel fuzzy numbers that can better model the uncertain parameters of the transportation system and the resulting uncertain variables.

We accept all kinds of fuzzy optimization models that can effectively address the transportation planning in a fuzzy environment. We also welcome any defuzzification methods that can make the transportation planning under uncertainty solvable, including but not limited to the fuzzy chance-constrained programming, fuzzy ranking approach, and robust optimization. Both exact solution algorithms and heuristic algorithms can be used to solve the transportation planning problems, in which any kinds of programming software can be adopted to realize their application in either empirical cases or numerical experiments. System simulation that can support the verification of feasibility of the fuzzy optimization in the transportation planning under uncertainty also falls into the scope of this Special Issue.

We welcome both research articles and review articles on “Advances in Fuzzy Optimization for Transportation Planning Under Uncertainty”.

Dr. Yan Sun
Prof. Dr. Maoxiang Lang
Guest Editors

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• transportation planning
• transportation optimization
• uncertainty modeling
• fuzzy set theory
• fuzzy optimization