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This study focuses on solving the green economic load dispatch problem by considering the presence of green energy sources, including wind energy and solar power plants. The main objective function of the whole study is to minimize the total fuel cost (TFC) of all the thermal generating sources (TGSs) in the system. Moreover, the multiple selection of all TGSs is also evaluated. Fire hawk optimization (FHO) and the Zebra optimization algorithm (ZOA) are applied to solve the problem of achieving the best TFC value and satisfying all the constraints involved. The results indicated that ZOA can achieve a better optimal solution compared to FHO. Particularly, the results obtained by ZOA are completely superior to FHO in all comparison criteria at two load demand levels, such as Best TFC value (Best.Cost), Average TFC value (Aver.Cost), and Maximum TFC value (Max.Cost). On top of that, ZOA is the only algorithm of two applied ones providing the fast convergence capability to the optimal value of the main objective functions in two cases of load demand levels. Therefore, ZOA is an efficient search method to deal with such GELD problems.

Company CV. AM Nanda Putra is located in Sidoarjo and operates in the scaffolding industry. Currently the company is experiencing losses due to a lack of optimization in planning the amount and time of ordering raw materials, which results in shortages and excess material inventory. To overcome this problem, the company uses the MRP (Material Requirement Planning) method in optimizing raw material planning. In terms of the lot sizing approach, the company applies the LFL and EOQ methods. The forecasting methods used are Moving Average (MA), Weight Moving Average (WMA), and Exponential Smoothing (ES). The smallest MAD results were obtained using the Exponential Smoothing (ES) method for all scaffolding products. The forecasting results are obtained to determine the MPS (Master Production Schedule) for the next 10 months. After the determination of  MPS, the results of Material Requirement Planning (MRP) were obtained, namely the supply of raw materials for MF 170 AM scaffolding of 35402 units or 17700 sets, MF 170 K1 scaffolding of 28906 units or 14453 sets, MF 190 AM scaffolding of 16250 units or 8125 sets, and MF 190 K1 scaffolding of 7656 units or 3828 sets. From the results of calculating the cost of raw material requirements using the Lot for Lot (LFL) method and the Economic Order Quantity (EOQ) method, it can be seen that the total cost of planning the smallest raw material inventory with an amount of Rp. 12,975,818,022.