|行政院主計處為調查國情於94年度辦理第11次農林漁牧業普查，舉辦之目的在於蒐集農林漁牧業資源分布、生產結構、勞動力特性、資本設備及經營狀況等最新基本資料，以作為政府施政及規劃農林漁牧業發展依據，而人力指派為普查作業中重要的環節，人力指派得宜將使人力於普查期發揮最大效力。惟現實環境中有關人力之作業調派工作多借由人工經驗主導調派，缺乏以系統化、科學化之數據分析，自然更談不上比較與評估，往往是浪費人力資源之主因其結果必造成普查期無法掌握。然而有關農林漁牧業普查作業最佳化之研究論述卻寥寥可數，實有深入研究之必要。 針對上述問題，本研究以農林漁牧業普查之人力指派模式為研究範圍，以整數規劃為架構，建立一套數學最佳化模式，依普查之完成期限需求、人力組合資源並依作業特性訂定各項限制條件之參數，利用LINGO 7.0套裝軟體撰寫電腦程式，求解出最小距離成本與人力組合之指派。本研究並對各項影響最小距離成本之參數作一敏感度分析，以瞭解因實務狀況改變，各參數變化對運算結果之影響程度。比較本研究模式和人工經驗指派方法為優，結果顯示本研究模式之效益顯著。 In order to update the information of resources distribution, structure of production, labor features, capital equipment and business operation in agriculture, forestry, fishery and husbandry, the Directorate-general of Budget, Accounting & Statistics, Executive Yuan implemented the 11th Agricultural , Forestry,Fishery and Husbandry Census in 2005 to make the public policy comprehensive and urge the development. However, the workforce assignment plays the most important part in every census and therefore, any census will operate well at the period of a survey from a good human resources plan. A systematic and scientific statistical analysis is excluded from the actual operation of the workforce assignment now and thus, the operation mostly depends upon the chief public servants’ experiences. So, there is even no room for a detailed comparison and assessment. The current practice not only leads to poor arrangement of human resources but poor gathering and incomplete coverage as well. Additionally, it requires a further research because there are only few theses on the optimized operation for census in agriculture, forestry, fishery and husbandry. The study aims at workforce assignment for census in agriculture, forestry, fishery and husbandry. A mathematically optimized model is established based on integer programming. Parameters including its deadline, workforce arrangement and operation features significantly affect this kind of survey. LINGO 7.0 is used to figure out the minimum cost between locations and optimized deployment of human resources. A sensitivity analysis is made in my study to make a better understanding of its practice and how parameters work in the results in attempt to locate if there are any other factors stimulating the minimum cost between locations. The findings show that this model works better than the actual operation through personal experiences and the national survey will benefit from it.