Deterministic processing time are no longer applicable under realistic circumstances because of the uncertainties involved in manufacturing and production processes. The present study aims to address ...

Candidates are frustrated. Employers are overwhelmed. The problem? An untenable pile of applications — many of them generated with the help of A.I. tools.

Implements job scheduling optimization using Genetic and Greedy algorithms. Includes performance comparison with Integer Programming. Evaluates processing time, efficiency, and accuracy in small-sc ...

This article comprehensively reviews the latest application progress of machine learning in multi-objective evolutionary algorithms for scheduling problems. We review various machine learning ...

This repo encapsulates a Python implementation of the Simulated Annealing Algorithm to solve by means of a "minimum energy state" heuristic the NP-hard n-machines|no preemption|C_max job shop ...

This paper studies a hybrid flow shop scheduling problem with reentrant jobs from a copper strip cold rolling process in copper plants. The objective is to find a near-optimal job sequences to ...