近年全球各區糊甘社會企業（Social Enterprises)逐漸發展，紛紛成立不少難顯「社會價值」與「商樂價值」 之社會企業國酷細織（以下簡稱社企），主要企業宗旨包括提出鯽繭業償式，同嘲平決現今社會議題、改善 人類生活或生存頃境等。本研究透過社企深度訪談、觀察與蒐集產主量資料，針對一有機農翱句社企個書長公司， 了萬噸日何經營阿里山與商投原住民農友之產銷班，社企除了需輔導農友種植有機農產品並提供穩定銷售通路， 協助農友在有機拇道土地上安心地在自己土地上耕種、生活。所以採取「保證收購」商業策略。但對於農友常性的農作過剩，社企卻面臨極大的產銷壓力。此外，社企個案公司多採用人工作業與工作表更新種植數量與採收歷史紀錄。另一方面，本研究希望改善一般社企屬於小型組織中人力成本吃緊的困境。因此，本研究建構農產品種植排程之創新服務與系統，自行研發農產種植排程系統，希望可同時幫助社企與農友彼此降低產銷不均的困境。農友也可有效率直接查詢排程系統之建議分配數量以執行種植工作，降低產量的不確定性。
本研究通用兩階段處理有機農產品種植排程，建立「模擬退火演算法」之最佳化模式，透過還算「降溫」 過程找出在同一溫度下，農友未收成量最小的農作物數量分配組合，並在數次降溫後達到最大鏈長及終止條件後得到的農友作物數量分配，即是農產品樹直「最佳化」的數量組合解。在進行模擬退火程序前，本研究採用社企個案公司之農友作物數量分配的真實資料，農友的作物收成率及歷年的種植數量來分配，將分配的結果當成模擬退火法之起始解，第二階段再使用模擬退火法的降溫過程找出未收成量最小的數量組合，且該數量組合的收成亮為最接近零售商的訂單量。本研究的種植排程服物系統的提出，不僅能提供最佳化的數量分配，進而取代人工排程作業，協助預估與分配農產種植數量，亦可改善產銷不均之關鍵問題。社企除提升原住民農業經濟，也更有餘力教育與行銷消費者健康有機農業之通路效能，實踐社會企業的宗旨。就服務科學而言，本篇貢獻於建立社企與農友的「價值共創」與「系統化服務創新」，為社企個案公司創造新的服務價值，亦可幫助社會企業的服務創新。

Social enterprises (SE) have increased and developed steadily for the past few years. Some enterprises or startups raise an integrating between business and socials values. Thus, the objective of SE is to solve the problems of social issues, improve human's life, and living environments. The research uses an agricultural SE that creates an innovative service with the aboriginal peasants who plant the organic products in their certification farmlands (i.e.,Aiisan and Nantou in Taiwan). The SE case mainly commits to provide these peasants a strategy of 'guarantee the acquisition', and made them work and live stably at themselves lands as poss ible. Obviously, the SE case needs to face with the high pressures of production and marketing. On the other hand, the most of SEs are small-scale enterprises with limited manpower. In order for understanding the operations between the SE and its suppliers (aboriginal peasants), the research adopts some deep interviews, observations, and data collections of production and marketing in order for developing a plant scheduling service system. This research intends to develop an effective plant scheduling service system to help solve the critical issue of ' balance of production and marketing' between the SE case and the suppliers. The users also can search for the system results to be the reference of the quantity and time schedule they need to plant. The system is capable of uncertainty decrease that can be viewed as a service innovation of social enterprise.
This research uses a two-stage optimization algorithm - ' Simulated Annealing (SA)' that is capable of computing the optimized quantity assignment based on the selling needs of SE. In the process of lower temperature, the methodology can attain the most chain length and stop condition to be the results of quantity assignment. Before the process of SA, the study firstly decides a set of initial solution according to the practical real data fi·om the real business case - A social enterprise of organic farming. The research refers to the combinations of all previous year crop rates and crop quantity. In the second stage, SA can search for the least quantity combination under the non crop rates and the sets of quantity will be closed to the order quantity of suppliers. Overall, this research contributes to an innovative service system which can generate the optimization of assigning crop quantity. Furthermore, the service system also can improve the manual operations, human cost down, and unbalanced production-marketing. From the service science perspective, the value co-creation can be really fulfilled between organic peasants and social enterprises. The research also represents how to create an innovative service value for the social enterprise.