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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
On the Optimality of Structured Policies in Countable Stage Decision Processes
No full textMulti-stage decision processes are considered, in notation which is an outgrowth of that introduced by Denardo [Denardo, E. 1967. Contraction mappings in the theory underlying dynamic programming. SIAM Rev. 9 165-177.]. Certain Markov decision processes, stochastic games, and risk-sensitive Markov decision processes can be formulated in this notation. We identify conditions sufficient to prove that, in infinite horizon nonstationary processes, the optimal infinite horizon (present) value exists, is uniquely defined, is what is called "structured," and can be found by solving Bellman's optimality equations: \epsilon -optimal strategies exist: an optimal strategy can be found by applying Bellman's optimality criterion; and a specially identified kind of policy, called a "structured" policy is optimal in each stage. A link is thus drawn between (i) studies such as those of Blackwell [Blackwell, D. 1965. Discounted dynamic programming. Ann. Math. Stat. 36 226-235.] and Strauch [Strauch, R. 1966. Negative dynamic programming. Ann. Math. Stat. 37 871-890.], where general policies for general processes are considered, and (ii) other studies, such as those of Scarf [Scarf, H. 1963. The optimality of (S, s) policies in the dynamic inventory problem. H. Scarf, D. Gilford, M. Shelly, eds. Mathematical Methods in the Social Sciences . Stanford University Press, Stanford.] and Derman [Derman, C. 1963. On optimal replacement rules when changes of state are Markovian. R. Bellman, ed. Mathematical Optimization Techniques. University of California Press. Berkeley.] where structured policies for special processes are considered. Those familiar with dynamic programming models (e.g., inventory, queueing optimization, replacement, optimal stopping) will be well acquainted with the use of what we call structured policies and value functions. The infinite stage results are built on finite stage results. Results for the stationary infinite horizon case are also included. For an application, we provide conditions sufficient to prove that an optimal stationary strategy exists in a discounted stationary risk sensitive Markov decision process with constant risk aversion. In Porteus [Porteus, E. On the optimality of structured policies in countable stage decision processes. Research Paper No. 141, Graduate School of Business, Stanford University, 71 pp., 1973, 1974, unabridged version of present paper.], of which this is a condensation, we also (i) show how known conditions under which a Borel measurable policy is optimal in an infinite horizon, nonstationary Markov decision process, fit into our framework, and (ii) provide conditions under which a generalized (s, S) policy [Porteus, E. 1971. On the optimality of generalized (s, S) policies. Management Sci. 17 411-426.] is optimal in an infinite horizon nonstationary inventory process.
Equivalent Formulations of the Stochastic Cash Balance Problem
No full textThis paper shows that the widely appearing "marginal cost" formulations of the dynamic, periodic review, stochastic cash balance problem are equivalent to a "total cost" formulation, as long as the holding, shortage cost, and "closing of account" functions are constructed correctly.
Some Bounds for Discounted Sequential Decision Processes
No full textNew bounds are obtained on the optimal return function for what are called discounted sequential decision processes. Such processes are equivalent to ones satisfying the contraction and monotonicity properties (Denardo [Denardo, E. V., 1967. Contraction mappings in the theory underlying dynamic programming. SIAM Review. Vol. 9, pp. 165-177.]). The bounds are useful primarily in the infinite horizon case. Certain subprocesses are exploited, based on the simple notion of taking only those states which are relevant into consideration. Some existing algorithms and some of their obvious extensions are listed. The possibility of identifying nonoptimal decisions, as in MacQueen [MacQueen, J. B., 1966. A Modified dynamic programming method for markovian decision problems. Journal of Mathematical Analysis and Applications. Vol. 14, pp. 38-43.], is included.
On the Optimality of Generalized (s, S) Policies
No full textA standard inventory model is examined with a concave increasing ordering cost function rather than simply a linear one with a setup cost. A generalized (s, S) policy is shown to be optimal in the n-period problem. A generalization of k-convex and quasi-convex functions to quasi-k-convex functions is required in the process. The probability densities of demand must be one-sided Pólya densities.
Investing in Reduced Setups in the EOQ Model
No full textThis paper is motivated by the observation that the Japanese have devoted much time and energy to decreasing setup costs in their manufacturing processes and that there has been little in the way of a formal framework available to use to think about such efforts. The object of this paper is to begin to provide such a framework. The framework developed identifies only one aspect of the advantages of reducing setups, namely reduced inventory related operating costs. The other advantages, such as improved quality control, flexibility, and increased effective capacity, are not accounted for in this paper. Nevertheless, substantial reductions in setups may be warranted based solely on the benefits identified in this paper. The approach taken here introduces an investment cost associated with changing the (current) setup level and adds a per unit time amortization of this cost to the other costs identified in the standard EOQ model. The general problem becomes that of minimizing the sum of a convex and a concave function. In two special cases, the minimization can be carried out explicitly. In one of these cases, numerous interpretations of the results are made, including comparisons of Japanese and American practices. For example, holding other parameters constant, there is a critical sales level such that investment is made in reducing setups if and only if the sales rate is above that level. When such investment is made, the optimal lot size is independent of the sales rate. The paper also addresses the joint selection of the setup cost and the sales rate. Selection of the sales rate is seen as incorporating explicit production and holding costs into the classical monopolist's pricing problem. An explicit solution is obtained for the model postulated.production/inventory, EOQ, operating characteristics
Technical Note—An Adjustment to the Norman-White Approach to Approximating Dynamic Programs
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