India's urban population will double in the 20 years between 1981 and 2001 and could then be as high as 350 million. The 12 cities already having over one million population are growing the fastest and the trends indicate that by the turn of the century there will be 5 megalopolitan areas of over ten million, 20 cities with more than one million and over 600 cities with over 100,000 people. Public transit is expected to handle about 75 percent of the travel in these cities. Like most developing countries, the urban form in India and road networks are not suited for modern traffic. It is concluded that: (1) Decongestion of core areas must be achieved while planned growth and provision of transport be part of urban planning; (2) Transport supply must be augmented while travel demand is reduced; (3) The predominance of low-income population makes public transport of utmost importance; (4) Pedestrians and cyclists must be considered as significant and inalienable traffic units; (5) Area development must include optimization of existing traffic facilities; (6) Transport mode planning must be part of an overall plan to achieve complementary road-rail coordination; (7) Operations research must be applied to every phase of public transit operations and planning; (8) Long-term financing must be established for long-term transit projects; (9) Planning of transport facilities must be geared to overall urban policy of scientific decentralization.
Urban transportation in America is undergoing a major appraisal and, emerging from these grassroots reappraisals, is a wealth of innovative ideas about the ways local transportation can be more effectively managed, provided, and paid for. These new approaches are divided into seven headings, and reviewed: (1) Developer involvement in transportation improvements; (2) Private-sector sponsorship of transportation services; (3) Transportation management associations; (4) Downtown transportation management; (5) Private operation of transit services; (6) Decentralizing service delivery; and (7) Private financing of transit infrastructure.
We are concerned with a class of organizations composed of a coordinating central system and plural semi-autonomous subsystems, such that each of them has a decision-making unit. Such a problem is regarded as that of a decentralized two-level optimization. The basic principle of planning for this organization is that the central system allocates resources so as to optimize its own objective, while the subsystems optimize their own objectives using the given resources.Within this framework of decision making, we consider a transportation problem in which N transport agents transport their own commodity. Each transport agent n, n=1, …, N, finds optimal flow patterns of the associated commodity n so that the transportation cost is minimized based on its own objective function under the arc capacity restriction imposed by the central agent. The coordinating central agent governs the transport agents through the way of allocating the arc capacity so that the optimality of whole network system is achieved. Here, the lower level problem is composed of a set of single commodity minimum cost flow problems of the transport agents, each of which can be easily solved separately by the subsystem.The decentralized optimization problem is solved in principle by a parametric approach. A feasible direction algorithm using directional derivative and application of a constraint simplex method are proposed to solve the formulated network flow problem.
Many policies use two categories of instruments: a financial incentive (most often a tax) for polluters, and direct undertakings or financing of some restorations or maintenances or improvements of environmental qualities. The financial consequences of such policies, when optimum, are important for considerations of public finance, decentralization (financial autonomy), and equity (must polluters pay?). They turn out essentially to depend upon the mathematical structure of, first, the environment function, i.e., the way in which qualities depend upon both deteriorating and improving activities, and, second, the various constraints of the problem. Constraints which can be expressed by functions homogeneous of any degree are shown to have no direct financial effect. Apart from the constraints' effects, budgetary equilibrium, surplus or deficit are respectively given by functions which present constant, decreasing, or increasing qualitative returns to scale, i.e., weighted homogeneity of degree zero, positive or negative. The opposite polar cases of cleaning and dilution types of improvement technology are presented, with some other mixed simple cases and a few examples of application of the results.