Production Scheduling (PS) is an essential paradigm within supply and manufacturing
systems and an important element of sustainable development. PS, mainly known for its …

Metaheuristics are general algorithmic frameworks, often nature-inspired, designed to solve
complex optimization problems, and they are a growing research area since a few decades …

This paper addresses scheduling of lot sizes in a multi-plant, multi-item, multi-period,
capacitated environment with inter-plant transfers. A real-world problem in a company …

The paper considers the problems of scheduling n jobs that are released over time on a
machine in order to optimize one or more objectives. The problems are dynamic single …

Purpose–This paper aims to introduce the efficiency improvement in the operating room
(OR) of a local hospital using the integration of simulation and optimization …

This paper deals with the heuristic solution of flexible flowshop scheduling problems with
unrelated parallel machines. A setup time is necessary before starting the processing of a …

Presently, companies live a reality of rapid economic transformations generated by
globalization. The growth of the products and services international trade, the constant …

We have used reinforcement learning together with Monte Carlo simulation to solve a
multiperiod production planning problem in a two-stage hybrid manufacturing process (a …

Abstract Metaheuristics such as Ant Colony Optimization, Evolutionary Computation,
Simulated Annealing, Tabu Search and Stochastic Partitioning Methods are introduced, and …

Huge amounts of data are collected nowadays from different application domains is not
feasible to analyze all these data manually. Knowledge Discovery in Databases (KDD) is the …