Dynamic Scheduling Knowledge for Meta-scheduling

When solving scheduling problems a crucial task is the selection or creation of the appropriate scheduling algorithm. An approach is presented that combines the use of meta-scheduling knowledge to select the appropriate strategy and the use of dynamic scheduling knowledge for the flexible creation of scheduling algorithms. The method is based on the decomposition of scheduling algorithms into their underlying strategies and heuristic rules for selection of appropriate orders, variants, operations or resources. The strategies are represented by means of planning skeletons and the heuristic rules in terms of rules. The refinement of abstract operators within a skeleton with the rules for selection generates again a scheduling algorithm. Therefore a huge library of different scheduling approaches is available due to the various possibilities for the dynamic combination of skeletons and rules. Meta-knowledge is used to select the appropriate skeleton and rules to be used within the skeleton regarding the given problem situation. The implementation leads to a hybrid scheduling system, providing the description and integration of different scheduling approaches and the support in selecting the appropriate ones. SCHEDULING The goal of scheduling is the temporal assignment of orders (e.g. for manufacturing products) to resources (e.g. machines) where a number of conditions have to be regarded. Scheduling covers the creation of a schedule of the production process over a longer period (predictive scheduling) and the correction of an existing schedule (or plan) due to actual events in the planning/ scheduling environment (reactive scheduling or rescheduling). Nearly the same information is needed for scheduling and rescheduling and the same conditions must hold for the result, e.g. concerning the goals to be fulfilled. meeting due dates), that should be fulfilled but may be relaxed. Result of scheduling is a schedule (or plan) showing the temporal assignment of operations of orders to the machines that shall be used. The problem space of scheduling can be represented as a heterogeneous AND/OR-tree. The nodes contain a statement about the contribution of the children nodes to the solution and a value of the type corresponding to the layer of the tree. Fig. 1 shows a graphical representation of the scheduling problem-including alternative production variants and machines. By integrating parameters like alternative variants or machines a more general view of scheduling is realized including some of the tasks of process planning. Finding a solution to the scheduling problem is equivalent to finding a solution of the AND/OR-tree where …