The aim of this paper is two-fold. Firstly, it seeks to compare the efficacy of the Malaysian integrated population (i.e., integration of family planning with health) program with its categorial family planning counterpart. Secondly, it attempts to identify the organizational factors and the ‘integration’ factors (operationalized as staff integrative linkages) that result in better program performance for the two programs. On the basis of effectiveness of family planning diffusion, the results of the analysis indicate that the Malaysian integrated population program is more effective than its categorial counterpart. Further, integrative linkage variables were found to be an important group of variables that results in the improved effectiveness of the integrated program. This suggests that future expansion of the Malaysian population program (and population programs of other developing countries in a similar stage of development as Malaysia) should be through the approach of integrating family planning services with the health network, rather than through the expansion of the categorial family planning organization.

The problem that we address is to determine the inventory stockage levels in a multi-echelon inventory system for a repairable item. In its simplest form the multi-echelon system consists of a set of operating sites supported by a centrally-located repair depot. Each operating site requires a set of working items and maintains an inventory of spare items. The repair depot also holds an inventory of spare items. Item failures are infrequent and are replaced on a one-for-one basis. In this paper we present an exact model for finding the steady-state distribution of the net inventory level at each site. This model assumes that the failures are generated by a compound Poisson process and that the shipment time from the repair depot to each site is deterministic. No assumptions are made with regard to the repair cycle at the depot. We contrast this model with existing models for these systems. Based on the exact model we present an approximation for the steady-state distribution for the case with ample servers at the repair depot. We show that this approximation is very accurate on a set of test problems.

When making decisions, managers like to obtain pertinent information quickly and accurately from the information systems in an organization. But, often, different answers are obtained, depending on how the information request is phrased or from which information system the information is requested. In order to correct this problem, the system analyst and data base administrator have to resolve any conflicts in defining elements, their names and their relationships before computerized information systems are designed. A syntax method, described in this paper, has been developed to handle this process. This method standardizes names and mathematical relationships of elements. These standard data elements become the input to most system analysis methods facilitating the design of computerized information systems.

The single machine sequencing problem is considered in which there are precedence constraints on the jobs. The objective is to minimize the sum of weighted completion times. A lower bound is obtained by successively performing a Lagrangean relaxation of appropriate constraints. Each Lagrange multiplier is chosen to provide the maximum increment to the lower bound subject to retaining the nonnegativity of the coefficients of the variables. When no further suitable constraints can be introduced into the Lagrangean function, the variables having zero cost coefficient are used to obtain a feasible sequence which provides an upper bound. The gap between the lower and upper bound is reduced by removing some constraints from the Lagrangean function and replacing them with others. This lower bounding procedure is used in a branch and bound algorithm. Computational results indicate that the algorithm can satisfactorily solve problems with up to 100 jobs.

Due to the combinatorial nature of the facility layout problem, current heuristic computer procedures do not always provide better solutions than visual methods. A new algorithm, FLAC (Facility Layout by Analysis of Clusters), is described which emulates the visual methods used by industrial engineers in solving facility layout problems. Initially side-stepping the combinatorial nature of the problem, FLAC is found to perform well in problems with high as well as low flow dominance, and in the presence and absence of line dominance. Computation time is attractive, especially on larger problems.

In this paper “Optimal and Near Optimal Price and Advertising Strategies,” Welam (Welam, Ulf P. 1982. Optimal and near optimal prize and advertising strategies. Management Sci. 28 1313–1327.) considers a model which is similar to a model analyzed by Gould (Gould, John P. 1970. Diffusion processes and optimal advertising policy. E. S. Phelps et al., eds. Microeconomic Foundations of Employment and Inflation Theory. W. W. Norton, 338–368.) in his work on optimal advertising policies. The main difference between the two papers is that while Welam's analysis is in discrete time, Gould's is in continuous time. The equivalence of the two analyses is easy to establish and is contained in Rao (Rao, Ram C. 1983. A note on optimal advertising strategies. Working paper, University of Texas, Dallas, January.).

This paper considers a multi-stage, serial inventory system. The demand for the end item is stochastic and stationary. The relevant costs include a fixed ordering cost and an echelon inventory holding cost for each stage, and a backordering cost for the end item. The objective is to find a continuous-review inventory control policy that minimizes the expected average costs. We present and analyze an approximate cost model. Our approximation is analogous to that for the traditional single-item, continuous-review inventory model that assumes a reorder-point, reorder-quantity policy. We obtain policies that are natural extensions to those for the single-item model.

A multiobjective integer programming model is presented for allocating an area of land for development. The objectives considered in the allocation are cost, proximity to desirable and undesirable land features and the shape of the area. An interactive multiobjective optimization algorithm is presented and applied to the model. The algorithm generates a subset of efficient solutions with some guidance from the decision maker at each iteration as to what constitutes a “preferred” efficient point. The algorithm calls for the frequent solution of subproblems which constrain all but one of the objectives while optimizing the remaining one. In the land allocation model, the subproblems are integer programs solved efficiently by specialized enumeration techniques. For some of the subproblems (namely, those using proximity as the single objective), the first feasible solution we enumerate is guaranteed optimal. For the other subproblems, we show that an algorithm with this fortunate property would require the solution of an NP-hard problem at each step of the enumeration. The model and algorithm were tested in locating potential sites for a 13-acre residential development within a 2250-acre study area near Norris, Tennessee.

This paper examines issues in building decision support models for budgeting nursing workforce requirements in a hospital. We determine regular-time, overtime, and agency workforce levels for various skill classes in a budget cycle. We introduce a family of eight models ranging from a single-period, aggregate and deterministic model to a multiperiod, disaggregate and probabilistic model. In a single-period model, we ignore the time-varying nature of demand for nursing hours. Aggregation is done over the nurse skill class mix. For probabilistic models, we consider demand uncertainty. Using empirical data, we evaluate the effects of level of sophistication in model building and in information requirements on their relative performances. The results suggest that ignoring the time-varying nature of demand does not induce gross errors in budget estimates. However, ignoring demand uncertainty produces underestimates (about five to six percent) of budget needs—a consequence of a Madansky (Madansky, A. 1960. Inequalities for stochastic linear programming problem. Management Sci. 6 197–204.) inequality. It also induces added costs to the system due to implementing nonoptimal regular-time workforce levels. Finally, we find that a simple formula using a single-period demand estimate gives excellent approximations to the budget estimates obtainable from the more precise models.

Certainty equivalence (CE) and probability equivalence (PE) methods are the two most frequently used procedures for constructing von Neumann-Morgenstern utility functions. In this paper, we compare these methods experimentally, using a two-stage within-subject design. By asking subjects first for a CE judgment and later for a related PE judgment (or vice versa), a consistency test is devised which any deterministic expectation model, including those allowing probability transformations, should meet. Using four related experiments, this consistency test is applied separately to gain and loss questions, and to the two sequences of linked equivalence judgments, namely CE-PE and PE-CE. The empirical results reveal serious inconsistencies between the CE and PE responses for each of the four experiments. The extent of discrepancy depends strongly on the subject's initial risk attitude and whether the gain or loss domain is examined. To explain the complex pattern of results, the second part of the paper explores several plausible hypotheses. The first of these concerns the role of random error, in either the responses or the utility function itself. It is shown that both can lead to bias, although not of a type that could explain our results. Thereafter shifts in reference points are examined. A particular reframing of the PE response mode is postulated in which a pure gamble is psychologically translated into a mixed one, leading to increased risk aversion. This hypothesis, which is also supported by other evidence, offers a complete and simple explanation of the results. Finally, several other behavioral hypotheses are examined, after developing a weighted average model to simulate them. They concern anchoring effects, differences in salience between the probability and outcome dimensions, strategic misrepresentation, regret or rejoice influences, and endowment effects. Although each hypothesis predicts some type of bias, none of these five could singly explain the particular pattern of bias observed. In general, the study demonstrates (1) that serious discrepancies exist between the CE and PE methods of utility measurement, (2) that the particular results are incompatible with traditional deterministic choice models, (3) how random response errors, through propagation, can induce systematic biases in the utility function, (4) that reframing of the PE mode offers a simple reference shift explanation of the complex findings, and (5) how various heuristics and biases can be operationalized and simulated to assess their effects on utility measurement. As such, this study represents a further step toward a systematic investigation of response mode biases in utility measurement.