qc-scheduling

Hybrid Classical-Quantum Optimization Techniques for Solving Mixed-Integer Programming Problems in Production Scheduling

Jobshop scheduling

Problem instances for the jobshop scheduling problem are in text format. They are arranged as follows:

***** Start text file *****

J(# jobs) M(# machines)

P(Processing times) : Matrix of dims |J|x|M|

C(Processing costs) : Matrix of dims |J|x|M|

R(Release time) : Vector of dim |J|

D(Due time) : Vector of dim |J|

***** End text file *****

Multipurpose batch scheduling

Problem instances for the jobshop scheduling problem are provided in the .npz format. These files can be read easily with the Numpy library in Python. Data in each instance can be accessed with the numpy.load function and the following keywords:

Data	Keyword
Tasks	I
Time points	N
Chemical material resources	R1
Equipment unit resources	R2
Set of tasks allowed for each equipment	Ir
Set of tasks that consume resources	Ti
Set of tasks that produce resources	To
Rate of generation	rho_I
Rate of consumption	rho_O
Minimum batch size	b_min
Maximum batch size	b_max