The job-shop scheduling problem (JSSP) is a challenging scheduling and optimization
problem in the industry and engineering, which relates to the work efficiency and operational …

Dispatching rules (DRs), which are simple constructive methods that incrementally build the
schedule, represent the most popular method for solving dynamic scheduling problems …

Genetic programming (GP) is one of the best approaches today to discover symbolic
regression models. To find models that trade off accuracy and complexity, the non …

Dynamic scheduling problems are important optimisation problems with many real-world
applications. Since in dynamic scheduling not all information is available at the start, such …

Linear genetic programming (LGP) has been successfully applied to dynamic job shop
scheduling (DJSS) to automatically evolve dispatching rules. Flow control operations are …

Scheduling is a frequently studied combinatorial optimisation problem that often needs to be
solved under dynamic conditions and to optimise multiple criteria. The most commonly used …

JSS (Job Shop Scheduling) is a significant and challenging combinatorial optimization
issue. Dispatching rules have been successfully used to determine scheduling decisions in …

The concept of green scheduling, which deals with the environmental impact of the
scheduling process, is becoming increasingly important due to growing environmental …

Dynamic multi-objective (MO) scheduling problems are encountered in various real-world
situations. Due to dynamic events that occur in such problems, one has to resort to using …

Genetic Programming (GP) is a well-known technique for generating dispatching rules for
scheduling problems. A simple and cost-effective local search technique for many-objective …