Ship Lock Scheduling

Features

• Problem input: Problem data will be read from XML files or generated randomly.
• Objective function: Above all, the waiting times of the ships should be minimized. There are also some other measures that can be weighted according to requirements.
• Optimization strategy: The major part is local search using several neighborhood types. Depending on the configuration, initial solutions will be improved by iteratively running hill climbing, some problem-specific postoptimization steps, and one worsening step.
• Configuration: The implemented algorithms can be selected, combined, and configured by a lot of parameters.
• Graphics: Displaying calculated solutions (screenshot 1) and calculations of algorithms (screenshot 2). These pictures can be saved as JPG.
• Flexibility: Manipulating solution data subject to restrictions.
• Analysis: Framework for analyzing the algorithms and calculated solutions: Generating test instances, parallel simulation, R/JGR code for multivariate data analysis (e.g. detemining best parameter values by statistical models).
• Analysis: Calculcating lower bounds for the cost of solutions.
• Analysis: Generating optimal solutions and comparing them with solutions found by local search.
• Analysis: Comparing solutions that have been calculated differently for the same problem instance.

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