Authors:
Sonja Breuß
;
Sven Löffler
and
Petra Hofstedt
Affiliation:
Chair of Programming Languages and Compiler Construction, Brandenburg University of Technology Cottbus-Senftenberg, Konrad-Wachsmann-Allee 5, Cottbus, Germany
Keyword(s):
Planning and Scheduling, Decision Support Systems, Stockyard Planning Problem, SPP, Constraint Programming, CSP, COP.
Abstract:
The stockyard planning problem (SPP) is a critical task in the global economy, involving the efficient transportation and storage of bulk materials such as iron ore or coal. At material turnover points such as harbors, the SPP optimizes when, where and which materials are unloaded from import vessels (imported), moved between areas on the stockyard (transported), loaded onto export vessels (exported) and mixed with other materials (blended). This is important for reducing mooring times of ships and meeting timely demands. The current approach to solving the SPP in real systems is manual, which is stressful and error-prone. This paper proposes a hybrid approach using both constraint programming and greedy search algorithms to solve the SPP. The proposed method splits the planning process into smaller problems, alleviating computational issues while maintaining overall solution quality.