This contribution introduces a mixed-integer programming formulation for the multi-level, multi-machine proportional lot sizing and scheduling problem. It also presents a genetic algorithm to solve that problem. The efficiency of that algorithm is due to an encoding of solutions which uses a...

This contribution summarizes recent work in the field of lot sizing and scheduling. The objective is not to give a comprehensive literature survey, but to explain differences of formal models and to provide some first readings recommendations. Our focus is on capacitated, dynamic, and...

This contribution generalizes the work of Drexl and Haase about the so-called proportional lot sizing and scheduling problem which was published in 1995. While the early paper considers single-level cases only, the paper at hand describes multi-level problems. 1t provides mixed-integer programs...

This contribution generalizes the work of Drexl and Haase about the so-called proportional lot sizing and scheduling problem which was published in 1995. While the early paper considers single-level cases only, the paper at hand describes multi-level problems. 1t provides mixed-integer programs...

This contribution introduces a mixed-integer programming formulation for the multi-level, multi-machine proportional lot sizing and scheduling problem. It also presents a genetic algorithm to solve that problem. The efficiency of that algorithm is due to an encoding of solutions which uses a...

This contribution summarizes recent work in the field of lot sizing and scheduling. The objective is not to give a comprehensive literature survey, but to explain differences of formal models and to provide some first readings recommendations. Our focus is on capacitated, dynamic, and...

This contribution presents two heuristic approaches for multi-level, single-machine lot sizing and scheduling. The first one is a variant of a so-called randomized regret based heuristic which is assumed to be the fastest available method for this particular class of problems. The second...