Learning to solve the single machine scheduling problem with release times and sum of completion times

Understand

In this paper, we focus on the solution of a hard single machine scheduling problem by new heuristic algorithms embedding techniques from machine learning field and scheduling theory.

• These heuristics transform an instance of the hard problem into an instance of a simpler one solved to optimality.
• The obtained schedule is then transposed to the original problem.
• Computational experiments show that they are competitive with state-of-the-art heuristics, notably on large instances.