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All Journal Journal of Robotics and Control (JRC) Journal of Research in Industrial Engineering and Management
Andi Cakravastia
Fakultas Teknologi Industri, Program Studi Teknik Industri, Institut Teknologi Bandung
Aerospace Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Other

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A Model of Proactive-Reactive Job Shop Scheduling to Tackle Uncertain Events with Greedy Randomized Adaptive Search Procedure Nisar, Muhammad Usman; Ma'ruf, Anas; Cakravastia, Andi; Halim, Abdul Hakim
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22208

Abstract

Despite substantial research on job shop scheduling (JSS), there is a gap owing to the lack of a unified framework that considers exact, heuristic, and metaheuristic methods for JSS. This study addressed this gap by presenting a comprehensive approach. The study offered following contributions in this regard: analyzed the exact optimization method for benchmarking, investigated a greedy algorithm (G_r A) for faster solutions, and implemented a novel Greedy Randomized Adaptive Search Procedure (GRASP) to achieve high-quality solutions with computational effectiveness. Additionally, this study considered serious dynamic events (SDE) such as new job arrivals (NJA), rush order (RO), machine failures (MF), and scheduled machine maintenance (SMM), as scheduling disruptions and proposed a proactive-reactive rescheduling strategy, with right-shift (RF) and regeneration (Reg) methods using a hybrid (periodic and event-driven) policy to tackle them. Results showed that the exact methods are optimal but computationally intensive, G_r A are faster but suboptimal, and GRASP strike a balance, delivering high-quality solutions with only a 3.43% gap from exact methods while maintaining computational efficiency. Additionally, RF method effectively handled MF, while Reg efficiently integrated NJA, RO, and SMM. Overall, this study offered a comprehensive approach to JSS, enhancing applicability in manufacturing environments.
Evaluasi Risiko yang Harus Dihadapi Vendor dalam Memenuhi Kebutuhan Permintaan Produk Perishable Bencana Gunung Api Menggunakan Simulasi Monte Carlo Prasetyo, Ikhsan; Cakravastia, Andi
Journal of Research in Industrial Engineering and Management Vol 2 No 2 (2024): November 2024
Publisher : Program Studi Teknik Industri, Fakultas Teknologi Industri, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61221/jriem.v2i2.42

Abstract

As a nation situated within the Pacific Ring of Fire, Indonesia is home to numerous volcanoes. Of the many active volcanoes present, approximately 40% are inadequately monitored. This situation positions Indonesia as one of the countries facing a significant threat from volcanic disasters. One of the critical challenges in disaster management lies in the logistics of disaster relief, particularly in managing perishable food supplies to meet the needs of affected victims. The handling of such logistical items must ensure that no expired products are utilized. One approach to addressing this challenge is to delegate management authority to third parties, specifically vendors who also handle daily demands. This strategy is intended to allow perishable products to be managed through rotation to fulfill all requests while vendors maintain vigilant oversight of existing inventory levels in warehouses. This research aims to evaluate the risks that a vendor must confront when implementing such a collaborative arrangement. The evaluation is conducted using Monte Carlo simulation to determine the optimal scenario that vendors can select. Analysis results indicate that the implementation of Scenario 2, which assumes that a disaster may occur once throughout the planning period, represents the most favorable scenario for vendors. The study underscores the importance of proactive disaster preparedness and efficient resource management in a country prone to volcanic activity. By exploring innovative approaches to logistics and inventory control, stakeholders can enhance their capacity to respond effectively to potential disasters, ultimately contributing to improved disaster resilience in Indonesia.
A Model of Proactive-Reactive Job Shop Scheduling to Tackle Uncertain Events with Greedy Randomized Adaptive Search Procedure Nisar, Muhammad Usman; Ma'ruf, Anas; Cakravastia, Andi; Halim, Abdul Hakim
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.22208

Abstract

Despite substantial research on job shop scheduling (JSS), there is a gap owing to the lack of a unified framework that considers exact, heuristic, and metaheuristic methods for JSS. This study addressed this gap by presenting a comprehensive approach. The study offered following contributions in this regard: analyzed the exact optimization method for benchmarking, investigated a greedy algorithm (G_r A) for faster solutions, and implemented a novel Greedy Randomized Adaptive Search Procedure (GRASP) to achieve high-quality solutions with computational effectiveness. Additionally, this study considered serious dynamic events (SDE) such as new job arrivals (NJA), rush order (RO), machine failures (MF), and scheduled machine maintenance (SMM), as scheduling disruptions and proposed a proactive-reactive rescheduling strategy, with right-shift (RF) and regeneration (Reg) methods using a hybrid (periodic and event-driven) policy to tackle them. Results showed that the exact methods are optimal but computationally intensive, G_r A are faster but suboptimal, and GRASP strike a balance, delivering high-quality solutions with only a 3.43% gap from exact methods while maintaining computational efficiency. Additionally, RF method effectively handled MF, while Reg efficiently integrated NJA, RO, and SMM. Overall, this study offered a comprehensive approach to JSS, enhancing applicability in manufacturing environments.
Co-Authors A. Hakim Halim Abdul Hakim Halim Bermawi P. Iskandar Docki Saraswati Hidayat, Nita P.A Ma'ruf, Anas Nisar, Muhammad Usman Prasetyo, Ikhsan T.M.A Ari Samadhi, T.M.A Ari