Recently, The issue of energy consumption has become an issue that is often considered, and the manufacturing sector contributes to the most significant proportion of this problem. Energy-Efficient Permutation Flow Shop Scheduling Problem (EEPFSP) is an effective way to solve this problem. This research offers a new algorithm Hybrid Multi-Verse Optimizer Algorithm (HMVO). Siz experiments are presented to minimize total energy consumption. In addition, the Genetic algorithm (GA) and Ant Colony Optimization (ACO) algorithms were used as comparison algorithms. The experimental results show that HMVO requires low iterations to solve small and medium EEPFSP cases. However, the proposed algorithm requires large iterations to solve large case problems. In addition, the HMVO algorithm is more effective than GA and ACO in solving EEPFSP problems.

Selecting or evaluating reliable suppliers is essential to business, and the food industry is no exception. Business operations are at serious risk if suppliers are not properly selected. One of the risks that occur is the risk of food safety and halal. Not many studies have explored this topic, even though this issue is crucial for the Muslim community. This research aims to Evaluate Supplier Involve in Food Safety and Halal Criteria using Fuzzy AHP. It can help food manufacturers decide based on food safety and halal criteria during the supplier selection. The case study is applied to a food industry in Indonesia that produces biscuits. Eight criteria and 17 sub-criteria based on economic, social, and environmental dimensions were used to evaluate suppliers. The results show that the Halal certification system (HP) and product compliance with specifications (Q2) are the most important factors to consider. Third and fourth places are product price criteria (C1) and food safety management system certifications (FS2). Weighted evaluations of food industry suppliers are also possible with Fuzzy AHP.