Work

Optimizing Production Scheduling in Smart Manufacturing Systems Using Hybrid Simulation-Based Multi-Objective Optimization

Year: 2025

Type: conference-paper

Abstract: is In the era of Industry 4.0, optimizing production operations under dynamic and uncertain environments has become a critical challenge. This study presents a hybrid optimization framework combining discrete-event simulation (DES) and a multi-objective metaheuristic algorithm to enhance production scheduling in smart manufacturing systems. The proposed model addresses trade-offs between throughput, energy consumption, and machine utilization, enabling real-time adaptive decision-making. Experiments were conducted on a flexible job shop scenario, with results indicating significant improvements in operational efficiency compared to conventional heuristics. The research highlights the potential of integrating simulation-based optimization for robust and sustainable production operations.

Source: Proceeding of International Conference on Science and Technology UISU.

DOI: 10.30743/kgar4363

Authors: Derlini Derlini, Selly Annisa, Zulkarnain Lubis

Institutions: Universitas Pembinaan Masyarakat Indonesia Medan, State University of Medan, North Sumatra Islamic University

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Universitas Negeri Medan