Sunduck Suh

Integrated Urban Systems Modeling: Theory and Applications

I Urban Form, Functions and Structure.- 1 Urban Systems and Systems Analysis.- 1.1 Why Urban Areas?.- 1.2 Measuring Exports from Urban Areas.- 1.3 Review on Urban Systems Models.- 1.3.1 Location Theory and Spatial Economies.- 1.3.2 Models of Urban Rents.- 1.3.3 Models of Regional Economics.- 1.3.4 Transportation Models.- 1.4 Urban Systems and Mathematical Programming.- 2 Determinants of Urban Structure.- 2.1 Suburbanization Trends.- 2.2 Intensive Use of Urban Land.- 2.3 The Role of Congestion in Urban Form and Structure.- 2.4 Concluding Remarks.- II Linear Programming Models and Applications.- 3 Integrated Urban Systems Model I.- 3.1 Introduction.- 3.2 Model Formulation: Postulates.- 3.2.1 Export Requirements of Urban Goods.- 3.2.2 Cost Minimizing Production Function.- 3.2.3 Leontief Fixed Coefficient Production Function.- 3.2 4 Commodity Flow System.- 3.3 Model.- 3.3.1 Exogenous variables.- 3.3.2 Endogenous variables.- 3.4 A Numerical Calculation.- 3.4.1 Input Data.- 3.5 Concluding Remarks.- 4 An Application: Zoning for a Metropolis.- 4.1 Introduction.- 4.2 Model Solution for a Metropolis.- 4.3 Formulating a Zoning Map: An Example.- 4.4 Concluding Remarks.- III Nonlinear Programming Models And Applications.- 5 Integrated Urban Systems Model II.- 5.1 Introduction.- 5.2 Postulates.- 5.2.1 Interzonal Passenger and Commodity Flow.- 5.2.2 User Equilibrium Route and Mode Choice.- 5.3 The Model.- 5.3.1 Exogenous Variables.- 5.3.2 Endogenous Variables.- 5.3.3 Model Development.- 5.3.4 Economic Interpretation of Optimality Conditions.- 5.4 Concluding Remarks.- 6 Solution Algorithms.- 6.1 Introduction.- 6.2 Solution Techniques for Network Equilibrium Model.- 6.3 Alternative Solution Techniques.- 6.3.1 Wilsons Iterative Balancing Method.- 6.3.2 Powells Hybrid Numerical Method.- 6.3.3 Comparisons of the Two Methods.- 6.4 An Alternative Solution Algorithm.- 6.4.1 Solution Algorithm: An Alternative.- 6.5 A Numerical Example.- 6.6 Concluding Remarks.- 7 Model Application to the Chicago Area: Existing Urban Form VS. Model Estimates.- 7.1 Introduction.- 7.2 Application to the Chicago Region: Data.- 7.2.1 Zone and Transportation System.- 7.2.2 Zone System.- 7.2.3 Highway Network.- 7.2.4 Export Zones and Export Handling Cost.- 7.2.5 Land Availability.- 7.3 Transportation Cost Functions.- 7.4 Nonsurvey Input-Output Method.- 7.4.1 Updating Tables.- 7.4.2 Removal of Imports.- 7.4.3 Conversion to Normalized Coefficients.- 7.4.4 Adjustment for Regional Trade Patterns.- 7.4.5 Commodity Aggregation.- 7.4.6 Calculating the Direct Requirement Table.- 7.5 Total Outputs and Exports.- 7.5.1 Total Outputs.- 7.5.2 Total Exports.- 7.6 Land/Capital Input Coefficients and Parameters.- 7.6.1 Land Input Coefficients.- 7.6.2 Capital Input Coefficients.- 7.7 Other Input Parameters.- 7.7.1 Agricultural Land Rent and Capital Rent.- 7.7.2 Trip Generation Factors.- 7.7.3 Auto Occupancy Ratio and Truck Loading Factor.- 7.8 Application to the Chicago Region: Model Estimates and Evaluation.- 7.8.1 Analysis of Convergence.- 7.8.2 Evaluation of the Model Estimates.- 7.9 Concluding Remarks.- 8 Impact Analysis of Network Changes on Urban Form and Structure.- 8.1 Introduction.- 8.2 Fluctuating Lake Levels and Their Transportation Implications.- 8.3 Long-Run Effects of Closing a Major Arterial Street.- 8.4 Concluding Remarks.- IV Future Directions for Integrated Urban Systems Modeling.- 9 Modeling Public-Private Interaction: Bilevel Programming Approach.- 9.1 Introduction.- 9.2 Bilevel Programming Problem.- 9.3 Bilevel Programming Models for Public-Private Interaction.- 9.4 Solution Algorithms: Review and Evaluation.- 9.4.1 Extreme Point Search Method.- 9.4.2 Kuhn-Tucker Approach.- 9.4.3 Descent Method.- 9.5 An Alternative Solution Algorithm.- 9.6 Numerical Analysis.- 9.6.1 Example 1.- 9.6.2 Example 2.- 9.7 Further Research Direction.- 10 Urban Systems Modeling: Retrospects and Prospects.- 10.1 Urban Systems Models Revisited.- 10.2 Urban Systems Modeling: Future Prospects.- 10.2.1 Changes in Urban Lifestyles.- 10.2.2 Subjects for Further Study.- 10.2.3 Emerging New Tools for Urban Systems Modeling.- A Sample Calculation for Example 1.- Author Index.

Toward Developing a National Transportation Planning Model: A Bilevel Programming Approach for Korea

The paper addresses specific issues associated with solving a bilevel transportation planning model in which public-private interaction is explicitly represented. Provisions for interaction between the public and private sectors in planning models would shed light on many important issues of planning strategy because the private sector pursues its own interests, while the public sector attempts to broaden public interests in a mixed economic system.Bilevel programming models have been applied to analyzing problems of managing natural resources, project selection, agricultural sector strategic planning, regional development and transportation network design. Most of the problems formulated thus far in bilevel programming frameworks, however, are small examples which are illustrative in nature due to the lack of efficient algorithmic procedures to solve the programming problems. In fact, none of available solution algorithms were actually tested for solving a large scale-real world problem.By reviewing and evaluating available literature, the paper strives to shed light on the issue of the extent to which bilevel programming approaches can explain public-private interaction in a mixed economic system. The paper also discusses issues on solving a large scale bilevel programming problem and attempts to contribute toward building a normative theory of ways in which resources are allocated in a mixed economic system.On this special occasion of paying tribute to Mischaikows contributions to Regional Science, particularly to his dedication to the enhancement of Regional Science in the Pacific Region, the paper also addresses issues toward developing a national transportation planning model for Korea in a bilevel programming framework.

Esman: An expert system for manufacturing site selection

Abstract The purpose of the paper is to design an expert system for site selection, particularly for manufacturing establishments funded by foreign investors. A prototype expert system, ESMAN: An Expert System for Manufacturing Site Selection, is developed using Personal Consultant Plus. It is demonstrated that not only can the knowledge and expertise of an urban and regional planner be codified in a system that can advise less experienced planners, but also that such a system can become an educational tool that benefits urban and regional planning students.

ESMAN: an expert system for manufacturing site selection

Since the establishment of the Office of Foreign Investment in 1975 in the United States Department of Commerce, foreign inward direct investments in the U.S. have rapidly increased. Foreign inward direct investments include those of nonbank U.S. affiliates of foreign companies. A U.S. affiliate is a U.S. business enterprise in which there is foreign direct investment; that is, in which a single foreign person owns or controls, directly or indirectly, ten percent or more of the voting securities of an incorporated business enterprise or an equivalent interest in an unincorporated business enterprise (U.S. Department of Commerce, 1985). In 1984, non-Americans had 527.6 billion dollars worth of direct investment in the U.S., of which about one-fourth was used in some form of manufacturing activity. Total foreign direct investment in the U.S. in 1974 was 26.5 billion dollars.

Model Application I: Measurement of Congestion Functions for Korean Highways

Travel cost, or in a more general sense, travel impedance, on a given highway link usually increases as the traffic flow increases.1 As traffic flow increases beyond a certain level, congestion takes place. In modeling a highway network with congestion effect, it is necessary to have a correct congestion function to account for increases in travel cost for the given highway environment. This highway environment includes driver characteristics, roadway conditions, and roadside activities. Different countries with distinctive demographic, economic, cultural, and behavioral characteristics might have unique congestion functions for their own environments.

National Development Plans and Planning Issues in Korea

The process of development in many countries is assumed to evolve through a series of stages.1 The nature of this process depends on a number of factors, including the structure of each country’s economy in terms of its endowed resources, the state of technology, the availability of entrepreneurial talent, and the individual country’s position in the world economy from the perspective of the competitiveness of its products on the world market.

Combined Input-Output and Commodity Flow Model: A Nonlinear Programming Formulation

Many developing nations have formulated and implemented national development programs to increase their national well-being.1 Korea began its first five-year development program in 1961 and successfully implemented its fourth FYDP in 1981, as described in previous chapters.

Model Applications: Formulating Highway Investment Strategies

Improvement of road conditions has become a major concern for many developing countries in the 1980s.1 Roads in many developing countries have deteriorated in the past decade due to their bearing heavier traffic loads than was originally intended for them, and funds have been allocated for expanding rather than maintaining the network (World Bank 1983)[13]. Thus, formulating investment priorities for road improvement has become an important component in national planning strategy, because transportation is vital to nations’ economies. Also, many countries face various problems from having allocated limited capital resources in the past to improving transportation facilities that have since deteriorated.

A National Transportation Development Planning Model

How can we model the proper interaction between transportation and the other economic systems?1 As described before, such a model will not only be necessary for developing programs for national development, but also will be needed in revising priorities and implementing program changes. National transportation development planning models fall into two categories: positive and normative, like other models for both mixed and planned economies. The usual view in mixed economic systems is that some goods and services are produced by the private sector and some by the public sector.

The Transportation Systems in Korea

During the five consecutive FYDP periods (1962–1986), the government of Korea invested heavily in infrastructure development, particularly on transportation.1 Almost half of the total budget was spent on transportation during the first FYDP period (1962–1966). The government invested heavily in railroad systems to provide greater accessibility to and within the seven special planning districts established during the first FYDP (1962–1966) period.