A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA) - Muhammad Ammar, Nik Mu’tasim; Mohd Fadzil Faisae, Ab Rashid (AIP Publishing, 2024)
The Hybrid Flow Shop Scheduling (HFS) topic regarding problem modeling and solution techniques has received wide attention. The HFS problem has been extensively researched due to its importance and complexity. This paper presents an optimization scheme for a case study on minimizing makespan and energy consumption in a hybrid flow shop scheduling problem. The HFS consists of a few production lines with several parallel machines in one or more stages. The significant difficulty is assigning work to specific devices at different locations. A case study was implemented with twenty-seven jobs in four stages comprising bending, lathe, milling, and wire-cut machines. The (EE-HFS) optimization has been carried out using the Multi-Objective Dragonfly Algorithm (MODA). The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). Five metrics were employed for comparison purposes: Error Ratio (ER), Spacing (SP), Maximum Spread (MS), computational speed (CS), and Generational Distance (GD). The MODA outperformed other algorithms based on the convergence metric and was on par with different algorithms for spacing and maximum spread metrics optimization results. In conclusion, these results are significant for Hybrid flow shop scheduling regarding the energy utilization model and MODA’s excellent potential to be implemented further in other combinatorial scheduling problems. This case study considerably benefits the company by revising its time and minimizing its daily energy use.