v0.2.0

Refactored the PyScheduling package according to the GECCO 2023 paper to include the following:

• Generic solvers classes
• Refactored common components to the core library
• Added listeners to track the solving process

v0.1.8

Refactored constraints representation, used plotly for gantt

v0.1.7

Added all 4 categories' generic problems, downgraded to python3.8

v0.1.6

This release covers PMSP and SMSP, it adds generic problems and methods to the Single Machine and Parallel Machines Scheduling Problems.

v0.1.4 (first public release)

This is the first public release, it comes with some bug fixes from previous version:

• Fixed Cmax for Flowshop and Jobshop
• Fixed import error when docplex and gurobi are not installed
• Added documentation website
• Published to pypi

v0.1.3

This release contains the 4 main scheduling problems: SMSP, PMSP, Flowshop and Jobshop. Multiple variants, constraints and objectives have been considered and many methods have been implemented.

Future improvements will focus on adding more variants, and implement basic methods for as much problems as possible.

pyscheduling aims to break the barrier to scheduling optimization and provide a simple API for solving the most common scheduling problems.

v0.1.2

Added structure for single machine problems and implement methods for the two problems 1 | | wi Ci and 1 | ri | wi Ci . These methods include the following:

• List heuristics (WSPT, WSECi, WSAPT ...)
• Local search operators (intra_insertion, swap)
• LAHC
• Iterative LS

v0.1.1

All methods implemented for Rm | Sijk | Cmax problem. These methods include the following heuristics:

• constructive
• list heuristics
• grasp
• meta-raps

And the following metaheuristics:

• LAHC
• SA, RSA
• Ant colony

v0.1.0

This first release contains some methods to sovle Rm | Sijk | Cmax including constructive and list_heuristics