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The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified. The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases. This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.

Understanding customers' preferences and preference structure is an important aspect of managing service applications. This paper develops a heuristic approach that includes a new preference elicitation procedure and two different value function models. The elicitation procedure makes no assumptions about the form of the preference structure of the decision maker (DM), is easy to understand, and does not take much time to complete. Then, two different models based on different assumptions about the DM's preference structure are developed to fit the elicitation procedure data. The Linear-Fractional Model assumes perfect substitution (linear indifference curves where the slopes can vary) and the Decision Utility Model assumes perfect complements (right-angled indifference curves). The paper develops the methods using an example of a park management problem. The models are tested in an exploratory experiment that demonstrates how to use the methods and techniques in a multi-criteria decision problem.

This paper analyzes the strategic calculations of an academic program when setting minimal quality requirements for applicants as an issue in planning a signaling strategy under certain structural conditions, such as a rapid growth of a higher education system. We present two versions of a signaling game between an academic program/institution, as the informed player, and a governmental controlling body that has incomplete information about the program's quality. One version describes a situation where there is low sensitivity to quality variations in the system and the second where there is high sensitivity to quality. Analysis shows that governmental controlling bodies can affect the quality of the system by influencing the sensitivity to quality rather than by direct and tight control over academic institutions. Given a certain level of sensitivity, the impact of these bodies on outcomes is minimal so their intervention in the market can be limited as well.

The time-to-market in the presence of a window of opportunity is analyzed using ;a probabilistic model, i.e. a model where the completion time of new product development is a random variable characterized by a gamma distribution. Two cases are considered: the first, a case where the discounted return-on-investment exceeds the return expected from a conservative investment—e.g. investment in bonds—termed ‘the profitable case’; and the second, a case where the discounted return-on-investment just balances the cost of new product development, termed ‘the salvageable case’. The model constructed is focused on the financial aspects of new product development. It allows a decision-maker to monitor, as well as terminate, a project based on its expected value (at any time prior to completion) by computing the mean time-to-market that provides profit, investment salvage, or loss. The mean time-to-market computed by the model may be compared with that estimated by the technology development team for decision-making purposes. Finally, in the presence of a window of opportunity and for the specific cases analyzed, we recommend to always keep the expenditure rate lower than the expected return rate. This will provide the decision-maker a salvageable exit opportunity if project termination is decided. Copyright © 2002 John Wiley & Sons, Ltd.

The location-allocation problem in its basic form assumes that the number of new facilities to be located is known and the capacities are unlimited. When the locations of the facilities and demand points (or customers) are restricted to the real line, the basic model may be solved efficiently by dynamic programming. In this note, we show that when the number of facilities and their capacities are included in the decision process, the problem may actually be easier to solve.

The problem we address involves locating p new facilities to service a set of customers or fixed points on the real line such that a measure of total cost will be minimized. A basic form of this problem was investigated by Love (1976), who observed that the fixed points must be allocated in sequence to the new facilities in an optimal solution, and thus, the problem can be solved by a dynamic programming algorithm. Since then, other forms of the model have been investigated; however, in all cases it is assumed that the new facilities have unlimited capacity so that customer flows are always allocated to the nearest facility. The objective of this paper is to analyze the effect of capacity constraints on the optimal locations of the new facilities. A general fixed-cost function is also included to account for practical considerations such as zoning regulations, and to permit the facilities to be located anywhere on the line instead of only at the fixed vertices. A dynamic programming method is formulated to solve the problem when the variable cost components are increasing convex functions of travel distance. The problem is shown to be NP-hard under more general cost structures.

We consider development projects in which the activities can be classified in two types: uncertainty resolving RD and routine technical investments which aim at improving the profitability of the project once the discovery has been made. The advantage of initiating routine preparatory activities prior to the achievement of a technological breakthrough in such projects, sometimes termed as ‘concurrent engineering’, is analyzed within a suitable dynamic optimization framework. The optimal double expenditure policy is compared with the conservative delayed investment policy, under which all the routine engineering activities are delayed until the risky R&D efforts culminate in a breakthrough. A criterion for the optimality of the latter policy is developed on the basis of the probability distribution of the discovery date. The application of the criterion is illustrated for a variety of specifications regarding the uncertainty associated with the R&D process. We find that simultaneous investment is the optimal policy for a large class of probability distributions. However, if the conditional probability of immediate discovery is always below some critical value, it is optimal to delay the preparatory activities until the discovery.

This paper explores the economic performance of the parallel path R&D approach to product innovation in the absence of patent protection. This is done within the context of a formal model in which competitive innovation is characterized as a dynamic game. The dynamic programming approach used by Aldrich and Morton [Manage. Sci. 21 (1975) 491] in the single firm case is extended here to a multi-firm market. Various measures (the expected net present value (ENPV) of total surplus and of profits, and the mean time to first innovation) are evaluated under different market structures. The study includes simulation analysis of the model.

The Dead Sea Works Ltd extracts more than 2 million ton of potassium a year from the Dead Sea and ships it by surface and marine transportation to markets around the world. Product mix and market distribution changes have made it necessary to redesign the surface logistics system. This system consists of four sites with a total of more than 300,000 ton of roofed storage capacity. The purpose of the study was to suggest changes in the storage capacity of each product at each of the sites. We have designed a model that expresses the expected annual loss for the firm and have solved it under potential market scenarios and management and technological constraints. Sensitivity analyses were then carried out for several uncertain cost and reliability parameters. Based on the best system configuration for each scenario, alternative configurations were designed in detail and compared under potential market scenarios. With a clear understanding of the risks and expected benefits involved, the decision makers then selected the best configuration. The annual net benefit from implementing the proposed solution is expected to be 1.7 million dollars.

Motion and time studies are an important component in Taylor's Scientific Management Approach. Time studies are extensively used in production industries, and they have also been used recently in service industries. Nevertheless, only a few applications of motion and time studies exist in the hospitality industry. This paper focuses on the challenges involved in applying motion and time studies to a hotel-room cleaning department. The second part of the paper employs stochastic process analysis for determining the steady-state probabilities of room status and, using the time standards from the first part, approximates labour requirements for effective room cleaning. The paper concludes with an evaluation of the applicability of time studies for hotels and with suggestions for future research.

In the paper we focus on the class of M/G/1 single vacation models, where a server takes exactly one vacation immediately after service completion and there are no items available in the system. This vacation model class includes model types with different vacation disciplines and, particularly, the exhaustive service model, gated non-exhaustive model, model with fixed vacation policy. Here we investigate the models that are characterized by the dependence of the item waiting time on the model parameters gained analytically or with the help of simulation. It is assumed that at the moment an item arrives into the system, there exists the probability, denoted as the a priori probability, that, according to some vacation discipline, the server takes a vacation after this item service completion. So we aim at deriving this a priori probability. To achieve the goal, we present some special M/G/1 model, which is equivalent to the mentioned above models, as far as the item waiting time is concerned. Within this special model the item flow is divided according to the Bernoulli recurrence operation with the parameter, associated with the a priori probability. Following this approach, the mentioned above models are differentiated from each other only by the a priori probability value. We introduce the examples of analytical and simulation approach for the a priori probability definition. The gained results widen the possibilities for analyses of the models being considered.

This paper provides confidence intervals for the probability of bankruptcy through the control of financial accounting variables. Our analysis differs in several aspects from standard bankruptcy techniques studied in previous studies. This bankruptcy literature generally provides classification techniques, peruses classification accuracy, and produces point estimators of bankruptcy for each firm. Various measures concerned with the confidence intervals are studied to evaluate the risk involved in predicting the probability of bankruptcy; for example, their maximum and minimum lengths, and their maximum lower bound and minimum upper bounds. We show that local minimum and maximum lengths are global. The empirical results illustrate a substantial improvement (reduction) in the length and the minimum upper bound of the confidence intervals at the optimal level of the financial accounting variables, whereas the lengths at the industry averages were significantly lower. The results are robust for three, two, and one year prior to bankruptcy.

Advertising may have a significant impact on a hotel's competitive advantage and financial performance. There is, however, an ongoing debate as to the role of advertising. One view suggests that advertising yields market power, which then fosters brand loyalty. The opposing view suggests that advertising, among other roles, is a method to inform customers about products or services, which then increases price sensitivity. This article discusses the hypothesis that the hotel's ability to communicate strategic assets determines the use of advertising. Hotels can use advertising channels to communicate strategic assets, hence create market power and support a price differentiation strategy. On the other hand, if the channel restricts the ability to communicate strategic assets, it will be used primarily as an informative tool. This study presents a case in which hotel advertisements are presented in a restricted setting, allowing advertising to communicate location and corporate affiliation, which a...

Rapidly growing higher education systems are often characterized by market failure in terms of programs' quality. When new institutions with various motivations enter the higher education market, and when applicants to these institutions are characterized by heterogeneous goals and motivations, acceptance criteria may differ among institutions. As a result, the quality of higher education may deteriorate. The current paper formally expresses this problem in a model for planning quality policy of academic institutions. Afterwards, an explanation is provided regarding conditions for setting national minimal quality requirements. This theoretical framework is applied to the Israeli higher education system, in an attempt to show that there is a market failure. Since controlling bodies do not have complete information about the quality of academic programs and there is low sensitivity to quality variations, high quality institutions do not have sufficient incentives to maintain high quality. Based on this analysis, policy implications regarding the required structural changes are drawn.

Gambling is a significant tourist attraction and provides a significant source for development to the region and the state, as well as an income to organizations in the tourism industry. Casino gaming is often considered a catalyst for the development of a tourism industry, providing new revenues, employment, and visitors. Many states debate whether gaming can or should become a part of their tourism industry. In this context, Israel is an interesting case. Although it has characteristics of a western culture in which the private enterprise gaming industry has gained increasing popularity, Israel was established as a Jewish state in which there is no division between state and religion. The purpose of this paper is to present a case for legalized gaming in Israel by focusing on the difficulties of the current situation, in which casino gaming is illegal. The paper also provides information on tangible benefits that might be expected from a legal gaming industry based on the private enterprise system. A hypothesized reality is investigated in which gaming is legal in Israel and a single casino is operating in the southern city of Eilat. The findings suggest that such a venture would generate economic benefits if policy makers provide a supporting legal setting in which illegal gambling is eradicated. The paper demonstrates how to initiate a cost benefit analysis of the issue in an effort to consider legal gaming in Israel.

Two cases of the discrete time finite horizon technology replacement problem are solved. The first deals with two available machines, one in use and a better one that can be purchased to replace it. The second case considers, in addition, a third machine of future technology that will be available at some random future time. The maintenance level of each used machine is chosen for each period in order to economically control performance deterioration. For solving the model, we first derive an optimal preventive maintenance policy by showing that “bang-bang” (i.e., full or non), non-increasing, maintenance efforts are optimal. Employing the optimal maintenance policy, we reformat the problem and conduct a numerical search in order to derive the replacement policy that will maximize the expected net present profit. Numerical examples demonstrate that management may improve profitability by delaying (but not necessarily foregoing) replacement with an available better machine.

We consider the production process of a manufacturing workcell. Production items obtained from an outside supplier are not processed adequately as far as their quality is concerned. Production items meeting the required quality depend on the workcell state, which degrades according to the number of produced items. The workcell is completely restored by some restoring operations leading to its as-new condition. The method of deriving the restoration period, which leads to the maximum probability that produced items meet the required quality, is introduced. It is based on the nontraditional approach, i.e. on the simplest strategies method for the formulation of the problem presented here. The implementation of this optimization approach is illustrated with an example.

In this paper, a multi-machine replacement problem is studied. T(1) represents an existing technology currently in operation; and machine T(2) represents a new technological breakthrough of which introduction time is uncertain. Economies of scale yield age-group based optimal replacement policies. This, in return, provides substantial reduction in the complexity of the problem. Sufficient conditions limit the amount of information needed to determine regenerative type optimal solutions to the infinite horizon problem.

The current study examines two recent developments in the production of soccer coverage in the Israeli media: (a) the introduction of “intellectuals” and soccer “jocks” to the soccer commentators’ booth, and (b) the debate about soccer commentary that has followed this trend. These developments are delineated from the perspective of the commentators themselves through in-depth interviews and a systematic survey of their statements in the media. The interpretations offered of the commentators’ accounts are multidimensional and draw on theories of postmodernity, social relations of power, and professional systems. While the engagement of these paraprofessional journalists in soccer commentating is seen to exemplify postmodern processes of de-differentiation, the debate about soccer commentary is also seen to reflect on the commentators’ class and professional background.

A new form of partial backorder policy (PB2) using two explicit backorder control limits and a intermediate time when dealing with shortages is introduced and parameterc analyses of various cost parameters of this policy are numerically explored. The traditional backorder policy, the lost sales policy, and a partial backorder policy using a single backorder control limit, called PB1, are special cases of PB2; hence a PB2 policy provides a unified frame work for studying different policies dealing with shortages. We provide an example where a PB2 policy produces a cost savings of 3.36% over the best of the pure backorder, the lost sales and the PB1 policies. Without the time dependent backorder cost, our PB2 policy will reduce to the PB1 policy. A cost savings of 6.63% is realized. This cost savings could be quite substantial for a firm with very large volume of business.

This paper deals with the decision making for resource sharing and scheduling for a class of computer-integrated manufacturing cells. Each such cell is characterized by a set of resources and it can be used for the cyclic production of several products. The production (processing) of each product requires a set of operations with sequence constraints among them. Each operation can be performed using alternative modes. Each mode defines the subset of resources needed for the operation and the timing of their use. Resource setup times are sequence-dependent. The problem is to choose the best mode for each operation and, accordingly, to allocate and schedule resources in order to minimize make-span time. A general (feasible) mixed 0–1 LP model is proposed. A customized Branch and Bound type solution algorithm is presented, which fathoms only feasible solutions and finds all optimum solutions.

The problem of determining the timing of risky R&D tasks (activities) and non-routine tasks is analysed through a simple non-linear mathematical programming model. The model ignores issues related to the flow of information gathered at each time point as a function of the amount of resources invested to this time point (see Lucas 1971, Management Science , 17 , 679-697, including his followers, and the literature on managerial economics for alternative approaches). The typical non-convex or non-concave structure of the objective function, which maximizes the expected discounted net value of the project, implies the possibility of multiple local optimal solutions. Forpracticalpurposes,theglobalsolution canbeidentified either by employing global optimization methods satisfying the K - T necessary conditions, i.e. Z (the gradient function of the objective function) 0, or by enumerating the objective value function for, at most, four basic solutions. An illustrative example indicates that solutions establishi...

The decision to invest in a new hotel near Jerusalem, Israel, is described and analyzed. Unlike most prescriptive models, reality dictated the ‘product’ as a hotel, as well as its general location. Consequently, a three-stage decision-making procedure was utilized. The analysis began with a specific site decision using an additive value function. Given the selected site, the second phase involved a thorough market study and a decision on the target markets. Finally, a business plan was presented. The entire process was carried out under the assumption of local resident acceptance of tourist development ventures in their area.

In this paper, a multi-machine replacement problem is studied. T(1) represents an existing technology currently in operation; and machine T(2) represents a new technology breakthrough of which introduction time is uncertain. Economies of scale yield age-group based optimal replacement policies. This, in return, provides substantial reduction in the complexity of the problem. Sufficient conditon limit the amount of information needed to determine regenerative type optimal solutions to the infinite horizon problem.

We present a taxonomy of the research that includes the relationship between quality and inventory. A literature review of over forty-five books and journal articles provides a basis for understanding the research in this area. Our goal is not to review all variants of this relationship or to describe all of the results, but rather to provide a broad overview of the major problems in the literature. We review optimization, statistical analysis and simulation, viewpoint and policy literature, although the majority of the works deal with optimization research and viewpoint or case studies. This is the first attempt to review this subjective matter.