Approximately 68 percent of the citizens of the world's developed countries live today in cities or in city-centered metropolitan areas. ¹ The economic and social fabric of these high-density clusters is elaborately interwoven, with the well-being of each citizen intricately enmeshed with the activities of others. Strong interdependencies arise in all areas of human need: food, shelter, safety, clothing, recreation, maintenance, energy provision, and so on. Servicing these needs requires highly structured transportation and communication networks throughout the city for effective provision of a variety of urban services: emergency medical, police, mail collection and delivery, fire protection, street and highway maintenance, utility repair, snowplowing, street cleaning, refuse collection, bus and subway transportation, taxi transportation, and so on.
Increasingly, citizens are demanding more urban services, by type, quantity, and quality. Yet the ability of most cities in the United States and elsewhere to pay for additional services has been severely strained during the 1970s. The resulting pressure, between the demands for more and better services, on the one hand, and decreased costs, on the other, has created a strong need for improved management decision making in urban services. It is a primary purpose of this book to provide methods for assisting these decisions.
United Nations Demographic Yearbook 1976. United Nations Department of Economic and Social Affairs Statistical Office, New York, 1977 (28th issue), Table 6, pp. 146-165.
For our purposes, a decision is an irrevocable allocation of resources.² Thus, this book will deal with the allocation or deployment of the resources of urban service systems, including personnel, equipment, and various service-improving technologies. From this viewpoint, urban operations research can be thought of as a decision-aiding technology, one to assist urban managers in improving the deployment of their resources. Most deployments occur spatially throughout the city, so much of our work will have a strong spatial component.
Urban operations research is not new. In 1736, the famous mathematician Leonhard Euler was confronted with an urban deployment problem when he attempted to find a feasible parade route over the seven bridges of Königsberg (now Kaliningrad) such that no bridge was crossed more than once. As argued in Chapter 6, Euler found the assignment impossible, but as a byproduct founded the extremely useful field of graph or network theory. Much more recently (1937), Merrill Flood of Columbia University is credited by George Dantzig and others as having stimulated serious interest in the traveling salesman problem (see Chapter 6) through his efforts to route school buses more efficiently. In the 1950s, Leslie Edie and his group at the New York Port Authority applied operations research methods to improve management of New York's tunnels and bridges, an activity for which Edie was awarded the first annual Lanchester Prize by the Operations Research Society of America (ORSA) for the best published work in operations research. Very significant progress in urban operations research has occurred within the last decade, spurred by the New York City Rand Institute and by research at MIT, the State University of New York at Stony Brook, Carnegie-Mellon University, the University of Maryland, Columbia University, and several other universities and organizations. Two of these efforts were awarded Lanchester Prizes by ORSA. Much of this recent work is made accessible herein, both in the text and in the end-of-chapter problems.
In the remainder of this chapter we provide a motivation for the material
in Chapters 2-8. Costs of providing services are always important, so in
Section 1. 1 we discuss the recent tendency for the costs of urban
services to grow at rates faster than those of many other sectors of the
economy. In Section 1.2 we present thumbnail sketches of situations in
which urban operations research methods are required to help analyze
various urban deployment problems. In Section 1.3 we discuss briefly the
steps that are necessary in undertaking any operations research study. Finally, in Section
1.4 we argue for the necessity of a probabilistic rather than deterministic
approach to most of the problems we will be addressing.