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In this paper we consider pathwise state constraint optimal control problems in which unknown parameters intervene in the dynamics, the cost, the endpoint constraint, and the state constraint. The cost criteria to minimize take an integral form of a given endpoint cost function with respect to a reference probability measure that is defined on the set of the unknown parameters. For this class of problems we derive necessary optimality conditions. [ABSTRACT FROM AUTHOR]

This study examines how optimal specific or ad valorem taxation in a free‐entry Cournot oligopoly market is affected by a change in another exogenously given tax. We derive the sufficient conditions for the uniqueness of the optimal tax rate, which are related to the concavity of the marginal revenue and the log‐concavity of the first derivative of the average cost function. By guaranteeing the uniqueness, we can conduct a comparative statics analysis on the optimal tax rate. We show that a marginal increase in another tax can paradoxically reduce prices and decrease the optimal tax rate. [ABSTRACT FROM AUTHOR]

In many real-life situations, the inventory record may not match the actual stock perfectly. This can happen due to distortion of inventory data, such as transaction errors, misplaced inventories, and spoilage. In these cases, because the decision maker only has incomplete information about the inventory levels, many well-known inventory policies are not even admissible, and our understanding of the optimal policies, even their existence, is very limited. In "Average Cost Optimality in Partially Observable Lost-Sales Inventory Systems," Bai et al. consider the classical lost-sales inventory model, in which the inventory level is only observed when it becomes zero. They formulate the cost-minimization problem as a partially observable Markov decision process. By exploiting the vanishing discount factor approach, they provide a way to verify the existence of optimal policies under the average cost criterion. The key step in their analysis is the construction of a valid policy, which, in a certain sense, copies the actions of another policy for the process starting from another initial state. We consider a partially observable lost-sales inventory system, in which the inventory level is observed only when it reaches zero. We use the vanishing discount factor approach to prove the existence of a stationary optimal policy for the average cost minimization. As our main methodological contribution, we provide a way to verify the key condition of the vanishing discount factor approach—the uniform boundedness of the relative discounted value function. To accomplish that, we construct a valid policy, which, in a certain sense, "copies" the actions of another policy for the process with a different initial state. To the best of our knowledge, this paper is the first one on partially observable inventory models under the average cost criterion. [ABSTRACT FROM AUTHOR]

We study the robustness of the c μ -rule for the optimal allocation of a resource consisting of one unreliable server to parallel queues with two different classes of customers. The customers in queues can be served with respect to a FIFO retrial discipline, when the customers at the heads of queues repeatedly try to occupy the server at a random time. It is proved that for scheduling problems in the system without arrivals, the c μ -rule minimizes the total average cost. For the system with arrivals, it is difficult directly to prove the optimality of the same policy with explicit relations. We derived for an infinite-buffer model a static control policy that also prescribes the service for certain values of system parameters exclusively for the class-i customers if both of the queues are not empty, with the aim to minimize the average cost per unit of time. It is also shown that in a finite buffer case, the c μ -rule fails. [ABSTRACT FROM AUTHOR]

This study examines whether and when Edgeworth's taxation paradox, that taxation decreases the equilibrium price, occurs in a free‐entry Cournot oligopoly with cost‐reducing investment. In contrast to the fact that no paradox occurs in the short‐run equilibrium, the paradox can occur in the long‐run equilibrium, in which the number of firms is endogenous. However, the conditions under which the paradox occurs are restrictive when there is no investment. By incorporating cost‐reducing investments into the model, we demonstrate that the paradox is likely to occur under less restrictive conditions, irrespective of whether the tax is specific or ad valorem. [ABSTRACT FROM AUTHOR]

The main objective of the land reform in Ukraine, which was launched 22 years ago, is to involve agricultural land in full, efficient, and transparent economic (market) turnover. During different stages of transformations in land relations, in scientific, political, and social circles, the issue of market turnover of agricultural land was particularly acute and always caused many disputes about precisely what the market turnover of land should be. With the introduction (from July 2021) of the market turnover of agricultural land, questions about its functioning not only remained, but, on the contrary, additional tasks were added: which model of market turnover Ukraine has chosen; what are the results of the functioning of the market turnover of agricultural land; whether the model of market turnover of agricultural land corresponds to the European integration direction of Ukraine’s development, etc. This study is focused on highlighting such issues, clearly revealing the essence of the subject through the analysis of statistical data, which in turn forms the relevance of the results presented. The purpose of the study is to cover and analyse the outcomes of the market turnover of agricultural land in Ukraine and to identify the existing issues. The purpose of the study is a comprehensive examination of the results of purchase and sale transactions of ownership rights to agricultural land plots concluded in Ukraine during 07/01/2021 – 07/01/2022 to determine the main trends in the results. The methods of analysis of the given subject were general scientific, including structural and functional (description and explanation of pricing and functioning of the market turnover of agricultural land); comparison (identification of discrepancies in the data of land value and the basis of its calculation on the basis of collected statistical data on the results of the market turnover of land), abstract and logical (generalisation and formulation of conclusions). Based on the findings, the results of the functioning of the market turnover of agricultural land were analysed, the causes of overstatement of land value were identified and the main price trends were established. The value of agricultural land is calculated by applying the median, the results are compared with the calculations of the average value. It is argued that the state authorities’ data on the value of agricultural land is calculated incorrectly. The number and structure of concluded contracts for the sale and purchase of agricultural land in the context of regions are investigated. The value indicators of agricultural land depending on the location, purpose and type of land are highlighted. The main difficulties in the functioning of the market turnover of agricultural land have been identified. Prospects for further research are to find solutions to the existing problems of market turnover of agricultural land by applying the findings of the study

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Optimal control problems are applied to a variety of dynamical systems with a random law of motion. In this paper we show that the random degradation processes defined on a discrete set of intermediate degradation states are also suitable for formulating and solving optimization problems and finding an appropriate optimal control policy. Two degradation models are considered in this paper: with random time to an instantaneous failure and with random time to a preventive maintenance. In both cases, a threshold-based control policy with two thresholds levels defining the signal state, after which an instantaneous failure or preventive maintenance can occur after a random time, and a maximum number of intermediate degradation states is applied. The optimal control problem is mainly solved in a steady-state regime. The main loss functional is formulated as the average cost per unit of time for a given cost structure. The Markov degradation models are used for numerical calculations of the optimal threshold policy and reliability function of the studied degrading units. [ABSTRACT FROM AUTHOR]

We study the robustness of the cμ-rule for the optimal allocation of a resource consisting of one unreliable server to parallel queues with two different classes of customers. The customers in queues can be served with respect to a FIFO retrial discipline, when the customers at the heads of queues repeatedly try to occupy the server at a random time. It is proved that for scheduling problems in the system without arrivals, the cμ-rule minimizes the total average cost. For the system with arrivals, it is difficult directly to prove the optimality of the same policy with explicit relations. We derived for an infinite-buffer model a static control policy that also prescribes the service for certain values of system parameters exclusively for the class-i customers if both of the queues are not empty, with the aim to minimize the average cost per unit of time. It is also shown that in a finite buffer case, the cμ-rule fails.

Our strategy is based on a novel reinforcement-learning (RL) Lyapunov methodology. We propose a method for constructing Lyapunov-like functions using a feed-forward Markov decision process. These functions are important for assuring the stability of a behavior policy throughout the learning process. We show that the cost sequence, which corresponds to the best approach, is frequently non-monotonic, implying that convergence cannot be guaranteed. For any Markov-ergodic process, our technique generates a Lyapunov-like function, implying an one-to-one correspondence between the present cost-function and the suggested function, resulting in a monotonically non-increase behavior on the trajectories under optimum strategy realization. We show that the system's dynamics and trajectory converge. We show how to employ the Lyapunov technique to solve RL problems. We explain how to employ the Lyapunov method to RL. We test the proposed approach to demonstrate its efficacy. [ABSTRACT FROM AUTHOR]

Discovering high utility sequences in a quantitative database is a popular data mining task. The goal is to enumerate all sequences of items (symbols) that have a high value for the user, as measured by a utility function. A representative application of high utility sequence mining is the identification of profitable sequences of purchases in transactions from online stores. Though useful, a drawback of that task is that the cost of items is not considered. However, cost is a key factor for decision-making in that domain and many others. To consider both the cost and utility of items for sequence mining, this paper defines a novel problem FLCHUSM of mining frequent sequences having a high average utility and a low average cost. Though the proposed problem is a generalization of the traditional problem of frequent sequence mining, it is more challenging because the average utility and average cost functions do not satisfy the downward-closure property traditionally used to reduce the search space. To offer a solution to this issue, this paper presents a lower bound on the cost and two novel upper bounds on the utility. Besides, four width, depth pruning, reducing and tightening strategies are devised to eliminate unpromising patterns from the search space. Taking these theoretical results as a foundation, a new CUL (Cost-Utility List) data structure is conceived for storing and quickly updating the utility and cost information of patterns, and a novel algorithm named FLCHUSPM is proposed for FLCHUSM . Results from several experiments show that FLCHUSPM is efficient in terms of memory usage and runtime, and that interesting patterns can be discovered in real data. [ABSTRACT FROM AUTHOR]

We consider the linear programming approach for constrained and unconstrained Markov decision processes (MDPs) under the long-run average-cost criterion, where the class of MDPs in our study have Borel state spaces and discrete countable action spaces. Under a strict unboundedness condition on the one-stage costs and a recently introduced majorization condition on the state transition stochastic kernel, we study infinite-dimensional linear programs for the average-cost MDPs and prove the absence of a duality gap and other optimality results. Our results do not require a lower-semicontinuous MDP model. Thus, they can be applied to countable action space MDPs where the dynamics and one-stage costs are discontinuous in the state variable. Our proofs make use of the continuity property of Borel measurable functions asserted by Lusin's theorem. [ABSTRACT FROM AUTHOR]

Copyright of Revista Visión Contable is the property of Universidad Autonoma Latinoamericana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Estimation of cost functions is an appropriate tool for optimal resource allocation in hospitals. The present study aimed at estimating cost function for hospitals affiliated to Shiraz University of Medical Sciences. Materials & Methods: In the current cross-sectional study, inputs, costs and resources data for 28 hospitals were gathered from hospital statistics and information system. Required data were collected monthly for two years (2015-2016). Then, The Cobb-Douglas cost function was estimated using panel data analysis. STATA 14 was used for data analysis. Results: Estimates showed that hospitalschr('39') cost elasticity concerning the inpatient and outpatient admission were 0.555 and 0.058 for large hospitals, and 0.769 and 0.099 for small hospitals (P

Optimal control problems are applied to a variety of dynamical systems with a random law of motion. In this paper we show that the random degradation processes defined on a discrete set of intermediate degradation states are also suitable for formulating and solving optimization problems and finding an appropriate optimal control policy. Two degradation models are considered in this paper: with random time to an instantaneous failure and with random time to a preventive maintenance. In both cases, a threshold-based control policy with two thresholds levels defining the signal state, after which an instantaneous failure or preventive maintenance can occur after a random time, and a maximum number of intermediate degradation states is applied. The optimal control problem is mainly solved in a steady-state regime. The main loss functional is formulated as the average cost per unit of time for a given cost structure. The Markov degradation models are used for numerical calculations of the optimal threshold policy and reliability function of the studied degrading units.

It is generally recognised that the present-value criterion should be preferred to the average-cost formulation in developing lot sizing models. Despite the advantages of the present-value measure, average-cost lot sizing models are far more widely applied. Because of the nature of the average-cost formulation, inventory carrying costs are evaluated according to a look-back approach, relying on historical values. In this regard, a general misconception in the inventory management literature concerned with average-cost models is that the unit stockholding cost rate should be established considering fixed warehouse costs, which are costs that are, in the short term, independent of the inventory level. This paper develops arguments supporting our belief that inventory carrying charges used in lot sizing models should take into account only those costs varying with the inventory level in the warehouse, and that considering fixed warehouse costs leads to pitfalls when making inventory replenishment decisions. To this aim, we first present an analytical treatment based on the classical Economic Order Quantity (EOQ) model, as its full analytical tractability permits us to better discuss the problem we are interested in. Finally, we present numerical experiments to assess the effect of the correct procedure to establish the unit stockholding cost rate on inventory management decisions. These experiments are performed considering warehouse costs taken from some industrial case studies presented in the literature. [ABSTRACT FROM AUTHOR]

This paper was motivated by a practical optimization problem that appeared in electricity market of Mongolia. We consider the total average cost minimization problem of power companies of the Ulaanbaatar city. By solving an identification problem, we developed a fractional model that quite adequately represents the real data. The obtained problem turned out to be a fractional minimization problem over a box constraint, and to solve it, we propose a method that employs the global search theory for d.c. minimization.

It is common in business analyses to invoke different efficiencies generated by scale. Growth is associated with declining average costs/sales and rising profit margins. Factors cited include the relatively fixed nature of some costs, increased bargaining power, and network effects. We investigate how different cost lines evolve for a sample of U.S. firms after their IPO. To our surprise, costs/sales do not generally decline and margins do not increase, even during the early years when growth is highest. We observe similar results for other samples of domestic and overseas firms, both public and private. We explore possible explanations for our results and discuss implications, especially for cost allocation and financial projections. JEL Classifications: G30; M13; M21; M41. Data Availability: Data are available from the public sources cited in the text. [ABSTRACT FROM AUTHOR]

We consider average-cost Markov decision processes (MDPs) with Borel state and action spaces and universally measurable policies. For the nonnegative cost model and an unbounded cost model with a Lyapunov-type stability character, we introduce a set of new conditions under which we prove the average cost optimality inequality (ACOI) via the vanishing discount factor approach. Unlike most existing results on the ACOI, our result does not require any compactness and continuity conditions on the MDPs. Instead, the main idea is to use the almost-uniform-convergence property of a pointwise convergent sequence of measurable functions as asserted in Egoroff's theorem. Our conditions are formulated in order to exploit this property. Among others, we require that for each state, on selected subsets of actions at that state, the state transition stochastic kernel is majorized by finite measures. We combine this majorization property of the transition kernel with Egoroff's theorem to prove the ACOI. [ABSTRACT FROM AUTHOR]

Background: Estimation of cost functions is an appropriate tool for optimal resource allocation in hospitals. The present study aimed at estimating cost function for hospitals affiliated to Shiraz University of Medical Sciences. Materials & Methods: In the current cross-sectional study, inputs, costs and resources data for 28 hospitals were gathered from hospital statistics and information system. Required data were collected monthly for two years (2015-2016). Then, The Cobb-Douglas cost function was estimated using panel data analysis. STATA 14 was used for data analysis. Results: Estimates showed that hospitals' cost elasticity concerning the inpatient and outpatient admission were 0.555 and 0.058 for large hospitals, and 0.769 and 0.099 for small hospitals (P<0.01). Among hospitals inputs, the cost of a physician with coefficient 0.175 in large hospitals and 0.481 in small hospitals (P<0.01) was most cost driver. In studied hospitals, average cost (36,406,480 Rial) was higher than marginal cost (26,548,020). Moreover, scale economies index were in small, large, and all hospitals were 0.868, 0.613 and 0.729, respectively. The number of active bed, length of stay and teaching activity had a positive effect on hospitals cost (P<0.01). Conclusion: According to the findings, to control costs, the hospital should manage most cost drivers, such as physicians and pharmaceutical costs. Moreover, According to the average and final cost and scale economies index, hospitals should expand their service provisions with current inputs and resources in order to reach the optimum point of output. [ABSTRACT FROM AUTHOR]

In stochastic dynamic games, when the number of players is sufficiently large and the interactions between agents depend on empirical state distribution, one way to approximate the original game is to introduce infinitepopulation limit of the problem. In the infinite population limit, a generic agent is faced with a so-called mean-field game. In this paper, we study discrete-time mean-field games with average-cost criteria. Using average cost optimality equation and Kakutani's fixed point theorem, we establish the existence of Nash equilibria for mean-field games under drift and minorization conditions on the dynamics of each agent. Then, we show that the equilibrium policy in the mean-field game, when adopted by each agent, is an approximate Nash equilibrium for the corresponding finite-agent game with sufficiently many agents. [ABSTRACT FROM AUTHOR]

The paper describes a new preventive maintenance approach for manufacturing systems under environment constraints. The manufacturing system under consideration consists of a machine M1 that produces a single product in a Just-in-Time context. To satisfy a constant demand d, the system called upon another machine M2 (the subcontractor), comprising the so-called environment, which produces at a certain rate the same type of product as M1. Both machines are subjected to random failures. Whereas machine M2 is uncontrollable from the maintenance point of view, an age-limit policy is used for preventive maintenance of machine M1. It is proved that the best age to perform preventive maintenance depends on the history of machine M1 and the state of M2. A numerical example is used to illustrate the proposed approach. [ABSTRACT FROM AUTHOR]