Maximo Scheduler Optimization leverage IBM® ILOG® CPLEX® Optimization Studio (COS) and the CP Optimizer solver.

IBM® ILOG® CPLEX® Optimization Studio uses decision optimization  technology to optimize your business decisions, develop and deploy optimization models quickly, and create real-world applications that can significantly improve business outcomes. https://www.ibm.com/products/ilog-cplex-optimization-studio

IBM ILOG CPLEX Optimization Studio is a prescriptive analytics solution that enables rapid development and deployment of decision optimization models using mathematical and constraint programming. 2 solvers are included:

• CPLEX Optimizer for mathematical programming (linear, mixed-integer and quadratic programming), addressing problems like long term production/maintenance planning e.g. assigning work to monthly time buckets https://www.ibm.com/analytics/cplex-optimizer
• CP Optimizer for constraint programming and constraint-based models, addressing efficiently scheduling problem e.g. deciding start and end time (at minute level for workorders) https://www.ibm.com/analytics/cplex-cp-optimizer

Maximo Scheduler Optimization uses CP Optimizer for the out of the box scheduling optimization models: GS (Graphical Scheduling), GA (Graphical Assignment), GSLP (Graphical Scheduling Large Project). CP Optimizer

• Provides modeling features specialized to scheduling like intervals decision variables (for activities) and cumul functions (for finite capacity resources)
• Support business goals by optimizing earliness and tardiness costs, duration costs
• Model the work breakdown structure of the schedule, task dependencies, setup/travel times…

CP Optimizer benefits includes a compact and maintainable formulations for complex scheduling problems, a highly optimized solution search: a continuously improving automatic search algorithm that is complete, anytime, efficient and scalable. The unique value of optimization is that you specify your constraints and objectives without describing how to come-up to a solution (so model can be extended)

With Maximo Scheduler Optimization (MSO) you can download COS if you want to develop and test your custom model or if you want to extend an existing model. Supported modeling languages are OPL, Java and Python. Custom or extended models can be deployed in MSO using the MSO admin console (or the REST API)