An Integrated Simulation-based Optimization Technique for Multi-Objective Dynamic Facility Layout Problem

TL;DR: In this paper, a survey of the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future is presented, motivated by the rich conclusions of this critical analysis, and select interesting open challenges for future research.

TL;DR: Industrial information integration engineering is a set of foundational concepts and techniques that facilitate the industrial information integration process and in recent years, many applicat...

TL;DR: The SVNWBPM and SVNWGBPM operators are used to solve the single-valued neutrosophic multiple attribute decision making problems and to verify the developed approach and demonstrate its practicality and effectiveness.

TL;DR: The proposed digital twin is continuously capable to predict the production status and provide information for monitoring of production performance thanks to the real time connections of the RTLS and adaptive simulation models.

TL;DR: Simulation results on five difficult test problems show that the proposed NSGA-II, in most problems, is able to find much better spread of solutions and better convergence near the true Pareto-optimal front compared to PAES and SPEA--two other elitist multi-objective EAs which pay special attention towards creating a diverse Paretimal front.

TL;DR: There is a disconnect between research in simulation optimization--which has addressed the stochastic nature of discrete-event simulation by concentrating on theoretical results of convergence and specialized algorithms that are mathematically elegant--and the recent software developments, which implement very general algorithms adopted from techniques in the deterministic optimization metaheuristic literature.

TL;DR: There is a disconnect between research in simulation optimization—which has addressed the stochastic nature of discrete-event simulation by concentrating on theoretical results of convergence and specialized algorithms that are mathematically elegant—and the recent software developments, which implement very general algorithms adopted from techniques in the deterministic optimization metaheuristic literature.

TL;DR: Both optimal and heuristic procedures are developed for this problem and are based on a dynamic programming formulation, which depends on the ability to solve the static problem efficiently.