ScheduleLab: An Eclipse/OSGi based platform for empirical analysis of stochastic local search algorithms solving resource Scheduling problems

There is a shortage of software development tools that support researchers in academia and industry alike in experimentation for performance evaluation of resource scheduling algorithms based on stochastic local search (SLS) techniques. Given their stochastic nature researchers rely on empirical techniques for performance analysis of SLS algorithms. This work contributes an effort to develop such a tool, called ScheduleLab, based on the Eclipse/OSGi platform. The class of SLS algorithms is expansive, so we focus our efforts on SLS algorithms solving resource scheduling problems to control the scope of the work. The tool is non-invasive to the developer's code base and extensible. The tool focuses on supporting problem instance generation and providing an experimentation harness for performance evaluation of such algorithms. We illustrate the utility of the tool with experimentation on algorithms that solve the job shop scheduling problem.