Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Lập trình tuyến tính và ứng dụng Kiểm tra Đi lại lãng phí và Bố trí các nhà cung cấp chăm sóc sức khỏe Chương này giới thiệu lập trình tuyến tính (LP), một kỹ thuật tối ưu hóa quan trọng trong phân tích và lập kế hoạch kinh tế xã hội. LP tìm kiếm để tối đa hóa hoặc giảm thiểu một chức năng khách quan để một tập các ràng buộc. Cả hai mục tiêu và hạn chế được thể hiện trong các chức năng tuyến tính. Nó chắc chắn sẽ có nhiều hơn một chương để trang trải. | 10 Linear Programming and Applications in Examining Wasteful Commuting and Allocating Health Care Providers This chapter introduces linear programming LP an important optimization technique in socioeconomic analysis and planning. LP seeks to maximize or minimize an objective function subject to a set of constraints. Both the objective and the constraints are expressed in linear functions. It would certainly take more than one chapter to cover all issues in LP and many graduate programs in geography planning or other fields use a whole course or more to teach LP. This chapter discusses the basic concepts of LP and emphasizes how LP problems are solved in SAS and ArcGIS. Section 10.1 reviews the formulation of LP and the simplex method. The method is applied to examining the issue of wasteful commuting in Section 10.2. Commuting is an important research topic in urban studies for its theoretical linkage to urban structure and land use as well as its implications in public policy. Themes in the recent literature of commuting have moved beyond the issue of wasteful commuting and cover a diverse set of issues such as the relation between commuting and urban land use explanation of intraurban commuting and implications of commuting patterns in spatial mismatch and job access. However strong research interests in commuting are to some degree attributable to the issue of wasteful commuting raised by Hamilton 1982 . A case study in Columbus OH is used to illustrate the method of measuring wasteful commuting and a SAS program is developed to solve the LP in the case study. Section 10.3 introduces integer linear programming ILP in which some of the decision variables in a linear programming problem take on only integer values. Some classic location-allocation problems such as the p-median problem the location set covering problem LSCP and the maximum covering location problem MCLP are used to illustrate the formulation of ILP problems. Applications of these .
