Documentation | Tutorials | Release Notes | 中文

python-lekin is a Flexible Job Shop Scheduler Library, named after Lekin. As a core function in APS (advanced planning and scheduler), it helps manufacturers optimize the allocation of materials and production capacity optimally to balance demand and capacity.

• Changeover Optimization
• Ready for demo, research and maybe production

• Multiple solving strategies:
  • Continuous Time Planning (CTP)
  • Construction Heuristics
  • Meta-heuristics (Genetic Algorithm, Simulated Annealing)
  • Reinforcement Learning
  • Operation Research methods
• Extensible architecture for custom solvers
• Comprehensive constraint handling
• Performance metrics and visualization
• Parallel solving capabilities
• Solution validation and verification

Installation

pip install lekin

Usage

from lekin import Heuristics, Rule
from lekin import Scheduler

solver = Rule('SPT')
scheduler = Scheduler(solver)
scheduler.solve(job_list, machine_list)

scheduler.draw()

In real world, Lekin integrates with MES to deploy production plans on the shop floor. Integration with ERP system is also required to exchange information on demand, inventory, and production

• Exhaustive search

  • branch and bound

• Construction heuristics

  • SPT
  • critical path

• Meta heuristics

  • local search
    • hill climbing
    • tabu search
  • evolutionary algorithms
    • genetic algorithms

• Operation search

  • or-tools

• Reinforcement learning

Metaheuristics combined with Construction Heuristics to initialize is the recommended choice.

from lekin.solver.constraints import BaseConstraint

class MyCustomConstraint(BaseConstraint):
    def check(self, solution):
        # Implement your constraint checking logic
        pass

@misc{python-lekin2022,
  author = {Hongying Yue},
  title = {python lekin},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/hongyingyue/python-lekin}},
}