PENJADWALAN FLOWSHOP THREE STAGE UNTUK MEMINIMASI KONSUMSI ENERGI MENGGUNAKAN YELLOW SADDLE GOATFISH ALGORITHM

Some manufacturing companies use batch flow shop production systems, for example in the beverage manufacturing process. The object of research has a three-stage production process where the main ingredients of the product are processed in batches at stage one and will be divided according to variants of the product at the next stage. Batch flow shop is a production system that processes product continuously with the same process and processes several products in the smallest unit size (batch). The problem is the occurrence of idle when dividing from batch to variant so that it affects the energy consumption. In this study, researchers propose a new algorithm called Yellow Saddle Goatfish Algorithm (YSGA) to solve energy consumption minimization problems. This batch production process occurs on one of the production machines. While other processes use flow shop permutations. To sort jobs from initialization position, the Large Rank Value (LRV) method is used. The best solution is obtained from the iteration experiments carried out. The conclusion obtained is the the proposed method (YSGA) has less energy consumption than the initial First Come First Serve (FCFS) method

A Novel Hybrid Yellow Saddle Goatfish Algorithm for Fuel Consumption Vehicle Routing Problem with Simultaneous Pick-up and Delivery Problem

Currently, the issue of the fuel crisis has become a global concern. The distribution sector is one of the sectors that consume the most significant fuel. Therefore, an effective procedure for fuel energy efficiency is needed to resolve the routing problem. In addition, the vehicle load must be considered in delivery and pickup at each node. This research proposes the novel Hybrid Yellow Saddle Goatfish Algorithm (HYSGA) algorithm to solve the Fuel Consumption Vehicle Routing Problem Simultaneous Pickup and Delivery (FCVRPSPD) problem. The objective function to be achieved was to minimize fuel costs. This study conducted experiments with HYSGA parameters such as the number of Goatfish, iterations, and the number of goatfish clusters to optimize the FCVRPSPD problem. In addition, a sensitivity analysis was presented to examine the effect of the FCVRPSPD variable on fuel costs. This study also compared the proposed algorithm with several state-of-the-art procedures. The results showed that the parameters of the number of Goatfish and the HYSGA iteration affected fuel costs. Furthermore, based on experiments, the proposed algorithm provided a competitive fuel cost compared to other algorithms