We have the great pleasure of inviting you to take part in The Fourth International Workshop on Dynamic Scheduling Problems, IWDSP 2023, to be held in Winterthur, Switzerland, June 5-6, 2023. The IWDSP 2023 workshop is organized jointly by Zurich University of Applied Sciences School of Engineering, Winterthur, Switzerland, and the Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznan, Poland.

The aim of this event is to present new results on dynamic scheduling problems, in which some parameters change in time. The list of topics related to the workshop scope includes scheduling with variable job processing times (controllable job processing times, time-dependent job processing times, position-dependent job processing times, resource-dependent job processing times, discrete-continuous scheduling, malleable task scheduling, scheduling pliable jobs), scheduling with various factors affecting job execution (ageing, alteration, deterioration, learning, shortening), scheduling on variable speed machines (energy-efficient scheduling, scheduling under time-of-use electricity tariffs, scheduling with rate-modifying activities, scheduling with maintenance activities), scheduling problems with constraints on processing speed or machine availability (scheduling with rate-modifying activities, scheduling on machines with non-availability periods of variable length), scheduling under uncertainty (robust scheduling, stochastic scheduling, scheduling with explorable uncertainty), scheduling with a partial, changing in time, data on jobs or machines (online scheduling, semi-online scheduling), and other scheduling problems with job or machine parameters changing in time. Other topics are not excluded, provided that they concern dynamic problems as above and may be applied to solving scheduling or related problems.

Organizers wish to make the workshop a forum for exchange of ideas related to various models of dynamically changing factors in different domains of scheduling theory and, in a broader sense, in operations research and combinatorial optimization.