In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting

foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different

weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal

preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best

organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple

cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling

problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated

problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data

simulating actual production parameters in one of the medium size foundry.

A novel approach for treating the uncertainty about the real levels of finished products during production planning and scheduling process

is presented in the paper. Interval arithmetic is used to describe uncertainty concerning the production that was planned to cover potential

defective products, but meets customer’s quality requirement and can be delivered as fully valuable products. Interval lot sizing and

scheduling model to solve this problem is proposed, then a dedicated version of genetic algorithm that is able to deal with interval

arithmetic is used to solve the test problems taken from a real-world example described in the literature. The achieved results are compared

with a standard approach in which no uncertainty about real production of valuable castings is considered. It has been shown that interval

arithmetic can be a valuable method for modeling uncertainty, and proposed approach can provide more accurate information to the

planners allowing them to take more tailored decisions.