Research Article Optimization of Joint Economic Lot Size Model for Vendor-Buyer with Exponential Quality Degradation and Transportation by Chimp Optimization Algorithm Dana Marsetiya Utama , Shanty Kusuma Dewi , and Sri Kurnia Dwi Budi Maulana University of Muhammadiyah Malang, Jl. Tlogomas No. 246, Malang 65144, East Java, Indonesia Correspondence should be addressed to Dana Marsetiya Utama; dana@umm.ac.id Received 19 June 2021; Revised 28 January 2022; Accepted 31 January 2022; Published 24 February 2022 Academic Editor: Harish Garg Copyright©2022DanaMarsetiyaUtamaetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Freight transportation plays a critical role in improving company performance in the modern manufacturing industry. To reduce costs, companies must take advantage of the use of large vehicles. It caused fewer deliveries, but inventory costs and degradation quality are high. One of the joint economic lot size (JELS) problems in supply chain is Integrated Single-Vendor Single-Buyer Inventory Problem (I-SVSB-IP). is study developed the I-SVSB-IP model that considers raw materials’ exponential quality degradation and transportation costs. e objective function of this research was to maximize the Joint Total Profit (JTP). ree decision variables used were inventory cycle time (T), raw material ordering frequency (m), and frequency of delivery of finished products to buyers (n). is study proposed a sophisticated Chimp Optimization Algorithm (ChOA) procedure to solve the I-SVSB-IP problem. A case study on the food industry in Indonesia was presented to optimize the I-SVSB-IP. e results showed that the ChOA procedure had produced an optimal solution compared to the state-of-the-art algorithm. is study also demonstrated a sensitivity analysis of decision and transportation variables to cost, revenue, and JTP. e results show that increasing transport frequency of ordering raw materials (m) and finished products to buyers (n) enhances the total cost and reduces joint total profit. In addition, increasing the rate of quality degradation of raw materials reduces JTP. 1.Introduction Currently, company performance is influenced by the effec- tiveness of supply chain management (SCM) [1–3]. SCM plays an essential role in integrating various company parts to in- crease competitive advantage [4, 5]. SCM is an approach used to incorporate decisions from upstream to downstream to minimize costs in the system [6]. Several efforts are made to improve company performance, such as advanced continuous replenishment, continuous partnerships, quick response, and integrated inventory decision [7, 8]. Integrated inventory is proven to have the best performance in many companies [9, 10]. e freight transportation problem has a vital role in improving company performance [11]. In general, research on fuel reduction in freight transportation is interesting to in- vestigate. One way to reduce fuel consumption is to minimize delivery frequency [12, 13]. Companies need to take advantage of the use of large vehicles to increase vehicle utilization to reduce costs. is decision impacts the low frequency of de- livery. However, the inventory costs incurred are high, causing high operating costs for the company [14–16]. In addition to transportation problems, the problem of decreasing quality is an important problem in inventory [17]. e decrease in the quality of raw materials impacts the quality of the finished product, which is not in accordance with company standards [18]. In addition, it also has an impact on high operational costs in the company. Excess raw material inventory causes deg- radation of raw material quality. Park [19] was the first re- searcher to develop an integrated production-inventory model for decaying raw materials. Unfortunately, this research as- sumes non-perishable raw materials. Many perishable products experience an exponential decline in quality. Hindawi Complexity Volume 2022, Article ID 9619530, 17 pages https://doi.org/10.1155/2022/9619530