This proof-of-concept study provides a novel method for robust-stable scheduling in dynamic
flow shops based on deep reinforcement learning (DRL) implemented with OpenAI …

A key challenge in production management and operational research is the flow shop
scheduling problem, characterized by its complexity in manufacturing processes. Traditional …

This paper addresses a bi-objective problem in flexible job shop scheduling (FJSS) with
stochastic processing times. Following the Just-In-Time philosophy, the first objective is to …

Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems.
Considering both types of uncertainties simultaneously makes optimization problems …

In this paper, we introduce a novel sim-learnheuristic method designed to address the team
orienteering problem (TOP) with a particular focus on its application in the context of …

There has been a significant increase in consumer credit worldwide in recent years. The
scheduling of jobs in credit factories is essential for speeding up the loan application …

This special issue of Algorithms is dedicated to recent developments of scheduling
algorithms and new applications. After the Special Issue on Algorithms for Scheduling …

Paper aims The objective of this paper is to investigate the effectiveness of a method, here
denominated the due date promise by slack time rule (DDPSTR), to evaluate its feasibility …

The current work contributes to stochastic hybrid flow shop scheduling. After a thorough
literature analysis, it is firstly evident that works on stochastic flow shop scheduling are still …

The current work contributes to stochastic hybrid flow shop scheduling. After a thorough
literature analysis, it is firstly evident that works on stochastic flow shop scheduling are still …