Scheduling has an immense effect on various areas of human lives, be it though its
application in manufacturing and production industry, transportation, workforce allocation, or …

Dynamic scheduling represents an important combinatorial optimisation problem that often
appears in the real world. The difficulty in solving these problems arises from their dynamic …

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

Many real-world applications of the vehicle routing problem (VRP) are arising today, which
range from physical resource planning to virtual resource management in the cloud …

Automatic programming (AP) is one of the most attractive branches of artificial intelligence
because it provides effective solutions to problems with limited knowledge in many different …

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 …

Genetic programming (GP) has been successfully introduced to learn scheduling heuristics
for dynamic flexible job shop scheduling (DFJSS) automatically. However, the evaluations of …

The optimized radial basis function network is a kind of neural network that utilizes a step
size inside of the gradient strategy for the modeling, where a small step size will spend much …

A scheduling problem for parallel batch processing machines (BPMs) with jobs having
unequal ready times in semiconductor wafer fabrication facilities (wafer fabs) is studied in …

Dynamic flexible job shop scheduling (DFJSS) is a critical and challenging combinatorial
optimisation problem. Genetic programming (GP) has been widely used to learn scheduling …