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Journal articles on the topic 'Cost bounded'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Haenni, Rolf. "Cost-bounded argumentation." International Journal of Approximate Reasoning 26, no. 2 (2001): 101–27. http://dx.doi.org/10.1016/s0888-613x(00)00063-3.

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2

Haslum, Patrik. "Heuristics for Bounded-Cost Search." Proceedings of the International Conference on Automated Planning and Scheduling 23 (June 2, 2013): 312–16. http://dx.doi.org/10.1609/icaps.v23i1.13597.

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The problem of searching for a plan with cost at most equal to a given absolute bound has attracted interest recently, and several search algorithms tailored specifically to this problem have been proposed. We investigate instead how to adapt planning heuristics to this setting. A few of the resulting heuristics, used in a greedy bounded-cost search, perform better than previous and baseline methods, but only by a small margin. Making effective use of the cost bound in bounded-cost planning, it appears, remains a challenge.

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3

Kim, Hyo-Sil, and Otfried Cheong. "The cost of bounded curvature." Computational Geometry 46, no. 6 (2013): 648–72. http://dx.doi.org/10.1016/j.comgeo.2012.10.008.

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Thayer, Jordan, Roni Stern, Ariel Felner, and Wheeler Ruml. "Faster Bounded-Cost Search Using Inadmissible Estimates." Proceedings of the International Conference on Automated Planning and Scheduling 22 (May 14, 2012): 270–78. http://dx.doi.org/10.1609/icaps.v22i1.13514.

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Many important problems are too difficult to solve optimally. A traditional approach to such problems is bounded suboptimal search, which guarantees solution costs within a user-specified factor of optimal. Recently, a complementary approach has been proposed: bounded-cost search, where solution cost is required to be below a user-specified absolute bound. In this paper, we show how bounded-cost search can incorporate inadmissible estimates of solution cost and solution length. This information has previously been shown to improve bounded suboptimal search and, in an empirical evaluation over

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Skyler, Shawn, Dor Atzmon, Ariel Felner, et al. "Bounded-Cost Bi-Objective Heuristic Search." Proceedings of the International Symposium on Combinatorial Search 15, no. 1 (2022): 239–43. http://dx.doi.org/10.1609/socs.v15i1.21774.

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There are many settings that extend the basic shortest path search problem. In Bounded-Cost Search, we are given a constant bound and the task is to find a solution within the bound. In Bi-Objective Search, each edge is associated with two costs (objectives) and the task is to minimize both objectives. In this paper, we combine both these settings into a new setting of Bounded-Cost Bi-Objective Search. We are given two bounds, one for each objective and the task is to find a solution within these bounds. We provide a scheme for normalizing the two objectives. We then introduce several algorith

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Kapoor, Sanjiv, and Mohammad Sarwat. "Bounded-Diameter Minimum-Cost Graph Problems." Theory of Computing Systems 41, no. 4 (2007): 779–94. http://dx.doi.org/10.1007/s00224-006-1305-z.

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Ebrahimnejad, Ali, Seyed Hadi Nasseri, and Sayyed Mehdi Mansourzadeh. "Bounded Primal Simplex Algorithm for Bounded Linear Programming with Fuzzy Cost Coefficients." International Journal of Operations Research and Information Systems 2, no. 1 (2011): 96–120. http://dx.doi.org/10.4018/joris.2011010105.

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In most practical problems of linear programming problems with fuzzy cost coefficients, some or all variables are restricted to lie within lower and upper bounds. In this paper, the authors propose a new method for solving such problems called the bounded fuzzy primal simplex algorithm. Some researchers used the linear programming problem with fuzzy cost coefficients as an auxiliary problem for solving linear programming with fuzzy variables, but their method is not efficient when the decision variables are bounded variables in the auxiliary problem. In this paper the authors introduce an effi

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Stern, Roni, Rami Puzis, and Ariel Felner. "Potential Search: A Bounded-Cost Search Algorithm." Proceedings of the International Conference on Automated Planning and Scheduling 21 (March 22, 2011): 234–41. http://dx.doi.org/10.1609/icaps.v21i1.13455.

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In this paper we address the following search task: find a goal with cost smaller than or equal to a given fixed constant. This task is relevant in scenarios where a fixed budget is available to execute a plan and we would like to find such a plan with minimum search effort. We introduce an algorithm called Potential search (PTS) which is specifically designed to solve this problem. PTS is a best-first search that expands nodes according to the probability that they will be part of a plan whose cost is less than or equal to the given budget. We show that it is possible to implement PTS even wi

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Li, Wengen, Jiannong Cao, Jihong Guan, Man Lung Yiu, and Shuigeng Zhou. "Efficient Retrieval of Bounded-Cost Informative Routes." IEEE Transactions on Knowledge and Data Engineering 29, no. 10 (2017): 2182–96. http://dx.doi.org/10.1109/tkde.2017.2721408.

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10

Vohra, Rajiv. "Marginal Cost Pricing Under Bounded Marginal Returns." Econometrica 60, no. 4 (1992): 859. http://dx.doi.org/10.2307/2951569.

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11

Hartmanns, Arnd, Sebastian Junges, Joost-Pieter Katoen, and Tim Quatmann. "Multi-cost Bounded Tradeoff Analysis in MDP." Journal of Automated Reasoning 64, no. 7 (2020): 1483–522. http://dx.doi.org/10.1007/s10817-020-09574-9.

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Abstract We provide a memory-efficient algorithm for multi-objective model checking problems on Markov decision processes (MDPs) with multiple cost structures. The key problem at hand is to check whether there exists a scheduler for a given MDP such that all objectives over cost vectors are fulfilled. We cover multi-objective reachability and expected cost objectives, and combinations thereof. We further transfer approaches for computing quantiles over single cost bounds to the multi-cost case and highlight the ensuing challenges. An empirical evaluation shows the scalability of our new approa

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Yin, Yi Lin, Zhi Chao Xu, and Qing Song Zou. "Research on Bias of Owner's Decision-Making in Risk-Sharing in Construction Project - A Perspective of Bounded Rationality." Applied Mechanics and Materials 357-360 (August 2013): 2164–70. http://dx.doi.org/10.4028/www.scientific.net/amm.357-360.2164.

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Bounded rationality has an important impact on owners decision-making of risk-sharing in the project. Based on the hypothesis of bounded rationality, the paper established a risk-sharing game model concerning owners reference dependency and loss aversion, as well as conducted the quantitative analysis. The finding shows that comparing with the hypothesis of rationality, if taking the ex-post transaction cost as reference, when owner considers that the cost of risk management is smaller, the bounded rationality would make the owner prefer the proper risk-sharing; when owner considers that the c

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13

Eberbach, Eugene. "$-Calculus of Bounded Rational Agents: Flexible Optimization as Search under Bounded Resources in Interactive Systems." Fundamenta Informaticae 68, no. 1-2 (2005): 47–102. https://doi.org/10.3233/fun-2005-681-203.

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This paper presents a novel model for resource bounded computation based on process algebras. Such model is called the $-calculus (cost calculus). Resource bounded computation attempts to find the best answer possible given operational constraints. The $-calculus provides a uniform representation for optimization in the presence of limited resources. It uses cost-optimization to find the best quality solutions while using a minimal amount of resources. A unique aspect of the approach is to propose a resource bounded process algebra as a generic problem solving paradigm targeting interactive AI

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14

Wright, Tommy. "A general exact optimal sample allocation algorithm: With bounded cost and bounded sample sizes." Statistics & Probability Letters 165 (October 2020): 108829. http://dx.doi.org/10.1016/j.spl.2020.108829.

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15

Parwani, Simran. "Optimal Route Search using Bounded Cost Informative Routes." International Journal for Research in Applied Science and Engineering Technology 7, no. 5 (2019): 3662–66. http://dx.doi.org/10.22214/ijraset.2019.5601.

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Al-Najjar, Nabil I., and Rann Smorodinsky. "Provision of a public good with bounded cost." Economics Letters 67, no. 3 (2000): 297–301. http://dx.doi.org/10.1016/s0165-1765(99)00275-x.

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17

Liu, Zhizhen, Hong Chen, Hengrui Chen, Xiaoke Sun, and Qi Zhang. "Trip Cost Estimation of Connected Autonomous Vehicle Mixed Traffic Flow in a Two-Route Traffic Network." Journal of Advanced Transportation 2020 (October 10, 2020): 1–10. http://dx.doi.org/10.1155/2020/8884732.

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With the advancement of connected autonomous vehicle (CAV) technology, research on future traffic conditions after the popularization of CAVs needs to be resolved urgently. Bounded rationality of human drivers is essential for simulating traffic flow precisely, but few studies focus on the traffic flow simulation considered bounded rationality in CAV mixed traffic flow. In this study, we introduce random bounded rationality into the hybrid feedback strategy (HFS) under CAV mixed traffic flow to explore the impacts of CAV penetration rate on the trip cost of vehicles. First, we investigated the

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18

Yeoh, W., A. Felner, and S. Koenig. "BnB-ADOPT: An Asynchronous Branch-and-Bound DCOP Algorithm." Journal of Artificial Intelligence Research 38 (May 23, 2010): 85–133. http://dx.doi.org/10.1613/jair.2849.

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Distributed constraint optimization (DCOP) problems are a popular way of formulating and solving agent-coordination problems. A DCOP problem is a problem where several agents coordinate their values such that the sum of the resulting constraint costs is minimal. It is often desirable to solve DCOP problems with memory-bounded and asynchronous algorithms. We introduce Branch-and-Bound ADOPT (BnB-ADOPT), a memory-bounded asynchronous DCOP search algorithm that uses the message-passing and communication framework of ADOPT (Modi, Shen, Tambe, & Yokoo, 2005), a well known memory-bounded asynchr

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19

Chan, Shao-Hung, Jiaoyang Li, Graeme Gange, Daniel Harabor, Peter J. Stuckey, and Sven Koenig. "ECBS with Flex Distribution for Bounded-Suboptimal Multi-Agent Path Finding." Proceedings of the International Symposium on Combinatorial Search 12, no. 1 (2021): 159–61. http://dx.doi.org/10.1609/socs.v12i1.18569.

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Multi-Agent Path Finding (MAPF) is the problem of finding collision-free paths for multiple agents. CBS is a leading optimal two-level MAPF solver whose low level plans optimal paths for single agents and whose high level runs a best-first search on a Constraint Tree (CT) to resolve the collisions between the paths. ECBS, a bounded-suboptimal variant of CBS, speeds up CBS by reducing the number of collisions that need to be resolved on the high level. It achieves this by generating bounded-suboptimal paths with fewer collisions with the paths of the other agents on the low level and expanding

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20

Cavazos-Cadena, Rolando, and Emmanuel Fernández-Gaucherand. "Value iteration in a class of average controlled Markov chains with unbounded costs: necessary and sufficient conditions for pointwise convergence." Journal of Applied Probability 33, no. 4 (1996): 986–1002. http://dx.doi.org/10.2307/3214980.

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This work concerns controlled Markov chains with denumerable state space, (possibly) unbounded cost function, and an expected average cost criterion. Under a Lyapunov function condition, together with mild continuity-compactness assumptions, a simple necessary and sufficient criterion is given so that the relative value functions and differential costs produced by the value iteration scheme converge pointwise to the solution of the optimality equation; this criterion is applied to obtain convergence results when the cost function is bounded below or bounded above.

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21

Fickert, Maximilian, Tianyi Gu, and Wheeler Ruml. "New Results in Bounded-Suboptimal Search." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 9 (2022): 10166–73. http://dx.doi.org/10.1609/aaai.v36i9.21256.

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In bounded-suboptimal heuristic search, one attempts to find a solution that costs no more than a prespecified factor of optimal as quickly as possible. This is an important setting, as it admits faster-than-optimal solving while retaining some control over solution cost. In this paper, we investigate several new algorithms for bounded-suboptimal search, including novel variants of EES and DPS, the two most prominent previous proposals, and methods inspired by recent work in bounded-cost search that leverages uncertainty estimates of the heuristic. We perform what is, to our knowledge, the mos

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22

Chang, Ray-I., Jui-Hua Tsai, and Chia-Hui Wang. "Edge Computing of Online Bounded-Error Query for Energy-Efficient IoT Sensors." Sensors 22, no. 13 (2022): 4799. http://dx.doi.org/10.3390/s22134799.

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Since the power of transmitting one-bit data is higher than that of computing one thousand lines of code in IoT (Internet of Things) applications, it is very important to reduce communication costs to save battery power and prolong system lifetime. In IoT sensors, the transformation of physical phenomena to data is usually with distortion (bounded-error tolerance). It introduces bounded-error data in IoT applications according to their required QoS2 (quality-of-sensor service) or QoD (quality-of-decision making). In our previous work, we proposed a bounded-error data compression scheme called

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23

Gözüpek, Didem, Hadas Shachnai, Mordechai Shalom, and Shmuel Zaks. "Constructing minimum changeover cost arborescenses in bounded treewidth graphs." Theoretical Computer Science 621 (March 2016): 22–36. http://dx.doi.org/10.1016/j.tcs.2016.01.022.

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24

KOSMIDOU, O. I. "Guaranteed cost control of systems with norm bounded uncertainties." International Journal of Systems Science 18, no. 9 (1987): 1637–44. http://dx.doi.org/10.1080/00207728708967141.

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25

Stern, Roni, Ariel Felner, Jur van den Berg, Rami Puzis, Rajat Shah, and Ken Goldberg. "Potential-based bounded-cost search and Anytime Non-ParametricA⁎." Artificial Intelligence 214 (September 2014): 1–25. http://dx.doi.org/10.1016/j.artint.2014.05.002.

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26

Valenzano, Richard, Shahab Jabbari Arfaee, Jordan Thayer, and Roni Stern. "Alternative Forms of Bounded Suboptimal Search." Proceedings of the International Symposium on Combinatorial Search 3, no. 1 (2021): 175–76. http://dx.doi.org/10.1609/socs.v3i1.18266.

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Previous research into bounded suboptimal search has focused on the development of epsilon-admissible algorithms which are guaranteed to return solutions that are no more than a factor larger than optimal. In this paper, we consider the problem of how to construct search algorithms that satisfy alternative types of guarantees such as an additive bound. This bounding paradigm requires that the cost of any solution found is no more than the optimal cost plus gamma, which is a user-defined constant. To this end, we provide theorems that define sufficient conditions for developing algorithms for a

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27

Hernandez, Carlos, Roberto Asin, and Jorge Baier. "Time-Bounded Best-First Search." Proceedings of the International Symposium on Combinatorial Search 5, no. 1 (2021): 97–104. http://dx.doi.org/10.1609/socs.v5i1.18325.

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Time-Bounded A* (TBA*) is a single-agent deterministic search algorithm that expands states of a graph in the same order as A* does, but that unlike A* interleaves search and action execution. Although the idea underlying TBA* can be generalized to other single-agent deterministic search algorithms, little is known about the impact on performance that would result from using algorithms other than A*. In this paper we propose Time-Bounded Best-First Search (TB-BFS) a generalization of the time-bounded approach to any best-first search algorithm. Furthermore, we propose restarting strategies tha

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Colmenares, W., F. Tadeo, E. Granado, O. Pérez, and F. Del Valle. "H2guaranteed cost control of discrete linear systems." Mathematical Problems in Engineering 6, no. 5 (2000): 425–37. http://dx.doi.org/10.1155/s1024123x00001411.

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This paper presents necessary and sufficient conditions for the existence of a quadratically stabilizing output feedback controller which also assuresH2guaranteed cost performance on a discrete linear uncertain system where the uncertainty is of the norm bounded type. The conditions are presented as a collection of linear matrix inequalities.The solution, however requires a search over a scalar parameter space.

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Gupta, Kavita. "On Some Aspects of Bounded Transportation Problem." Spectrum of Operational Research 3, no. 1 (2025): 310–18. https://doi.org/10.31181/sor31202648.

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This paper presents various aspects of the capacitated transportation problem by incorporating into the classical transportation problem some realistic constraints such as limited capacities, restrictions on total flow, time-sensitive delivery of goods, and linear, quadratic, and fractional objectives. It delves into cost minimization, time minimization, and the trade-off between these two aspects. A special class of non-linear programming problems such as the fixed-charge bi-criterion transportation problem with an indefinite quadratic objective function with restriction on total flow is exam

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TAYU, SATOSHI, TURKI GHAZI AL-MUTAIRI, and SHUICHI UENO. "COST-CONSTRAINED MINIMUM-DELAY MULTICASTING." Journal of Interconnection Networks 09, no. 01n02 (2008): 141–55. http://dx.doi.org/10.1142/s0219265908002205.

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We consider a problem of cost-constrained minimum-delay multicasting in a network, which is to find a Steiner tree spanning the source and destination nodes such that the maximum total delay along a path from the source node to a destination node is minimized, while the sum of link costs in the tree is bounded by a constant. The problem is NP-hard even if the network is series-parallel. We present a fully polynomial time approximation scheme for the problem if the network is series-parallel.

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31

Drgas-Burchardt, Ewa, and Anna Fiedorowicz. "Maximal Hypergraphs with Respect to the Bounded Cost Hereditary Property." Discussiones Mathematicae Graph Theory 25, no. 1-2 (2005): 67. http://dx.doi.org/10.7151/dmgt.1261.

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32

Gusfield, Dan, and Leonard Pitt. "A bounded approximation for the minimum cost 2-sat problem." Algorithmica 8, no. 1-6 (1992): 103–17. http://dx.doi.org/10.1007/bf01758838.

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33

Zhang, Jialin, and Wei Chen. "Bounded cost algorithms for multivalued consensus using binary consensus instances." Information Processing Letters 109, no. 17 (2009): 1005–9. http://dx.doi.org/10.1016/j.ipl.2009.06.004.

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34

Costanza, Vicente, Pablo S. Rivadeneira, and John A. Gómez Múnera. "An efficient cost reduction procedure for bounded-control LQR problems." Computational and Applied Mathematics 37, no. 2 (2016): 1175–96. http://dx.doi.org/10.1007/s40314-016-0393-x.

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35

Burkett, David, David Hall, and Dan Klein. "Optimal Graph Search with Iterated Graph Cuts." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (2011): 12–17. http://dx.doi.org/10.1609/aaai.v25i1.7829.

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Informed search algorithms such as A* use heuristics to focus exploration on states with low total path cost. To the extent that heuristics underestimate forward costs, a wider cost radius of suboptimal states will be explored. For many weighted graphs, however, a small distance in terms of cost may encompass a large fraction of the unweighted graph. We present a new informed search algorithm, Iterative Monotonically Bounded A* (IMBA*), which first proves that no optimal paths exist in a bounded cut of the graph before considering larger cuts. We prove that IMBA* has the same optimality and co

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36

Chen, Zhiwei, Shaoxu Song, Ziheng Wei, Jingyun Fang, and Jiang Long. "Approximating median absolute deviation with bounded error." Proceedings of the VLDB Endowment 14, no. 11 (2021): 2114–26. http://dx.doi.org/10.14778/3476249.3476266.

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The median absolute deviation (MAD) is a statistic measuring the variability of a set of quantitative elements. It is known to be more robust to outliers than the standard deviation (SD), and thereby widely used in outlier detection. Computing the exact MAD however is costly, e.g., by calling an algorithm of finding median twice, with space cost O ( n ) over n elements in a set. In this paper, we propose the first fully mergeable approximate MAD algorithm, OP-MAD, with one-pass scan of the data. Remarkably, by calling the proposed algorithm at most twice, namely TP-MAD, it guarantees to return

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37

Kotlar, Josip, and Philipp Sieger. "Bounded Rationality and Bounded Reliability: A Study of Nonfamily Managers’ Entrepreneurial Behavior in Family Firms." Entrepreneurship Theory and Practice 43, no. 2 (2018): 251–73. http://dx.doi.org/10.1177/1042258718796085.

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We use transaction cost economics to explain the individual-level entrepreneurial behavior of family and nonfamily managers in family firms. We argue that nonfamily managers exhibit lower entrepreneurial behavior than family managers, particularly after the founder’s departure from the business. Moreover, we identify an expanded set of factors through which family firms can facilitate nonfamily managers’ entrepreneurial behavior, including monitoring, incentives, distributive justice, access to the top management, and job control perceptions. We test these hypotheses in a sample of 296 family

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38

Guo, Xianping, and Liuer Ye. "New discount and average optimality conditions for continuous-time Markov decision processes." Advances in Applied Probability 42, no. 4 (2010): 953–85. http://dx.doi.org/10.1239/aap/1293113146.

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This paper deals with continuous-time Markov decision processes in Polish spaces, under the discounted and average cost criteria. All underlying Markov processes are determined by given transition rates which are allowed to be unbounded, and the costs are assumed to be bounded below. By introducing an occupation measure of a randomized Markov policy and analyzing properties of occupation measures, we first show that the family of all randomized stationary policies is ‘sufficient’ within the class of all randomized Markov policies. Then, under the semicontinuity and compactness conditions, we p

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Guo, Xianping, and Liuer Ye. "New discount and average optimality conditions for continuous-time Markov decision processes." Advances in Applied Probability 42, no. 04 (2010): 953–85. http://dx.doi.org/10.1017/s000186780000447x.

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This paper deals with continuous-time Markov decision processes in Polish spaces, under the discounted and average cost criteria. All underlying Markov processes are determined by given transition rates which are allowed to be unbounded, and the costs are assumed to be bounded below. By introducing an occupation measure of a randomized Markov policy and analyzing properties of occupation measures, we first show that the family of all randomized stationary policies is ‘sufficient’ within the class of all randomized Markov policies. Then, under the semicontinuity and compactness conditions, we p

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Siag, Lior, Ariel Felner, and Shahaf Shperberg. "Heuristics for Bounded-Suboptimal Search." Proceedings of the International Symposium on Combinatorial Search 18 (July 19, 2025): 145–53. https://doi.org/10.1609/socs.v18i1.35986.

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In heuristic search, it is well-established that different types of heuristics are suited for optimal heuristic search (OHS) and unbounded suboptimal search (USS). In OHS, the heuristic should minimize the error in estimating the true cost of the shortest path, whereas in USS, it is more beneficial for the heuristic to exhibit a clear gradient toward the goal, regardless of the error. However, no study has specifically investigated which heuristic is most effective for bounded suboptimal search (BSS), and the current standard is to use heuristics designed for OHS. This paper introduces a novel

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Wang, Neng Min, Zheng Wen He, and Lin Yan Sun. "Study on the Bounded Inventory Model with Returning Items and Disposals." Advanced Materials Research 102-104 (March 2010): 920–25. http://dx.doi.org/10.4028/www.scientific.net/amr.102-104.920.

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This paper addresses a dynamic lot sizing problem with mixed returning items and disposals and bounded inventory. The returning items mean that returns are in good enough condition to re-enter the inventory supply stream. The producing, the holding, backlogging and disposals cost functions are concave cost functions. Furthermore, backlogging level and inventory level at each period is limited. The goal is to minimize the total cost of production, inventory holding/backlogging and disposal. A dynamic programming algorithm with complexity O(T3) is developed to solve this model, where T is the le

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42

Atsmony, Matan, and Gur Mosheiov. "A Greedy heuristic for solving scheduling problems with bounded rejection cost." Computers & Operations Research 144 (August 2022): 105827. http://dx.doi.org/10.1016/j.cor.2022.105827.

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43

Li, Shu, Rami Melhem, and Taieb Znati. "An efficient algorithm for constructing delay bounded minimum cost multicast trees." Journal of Parallel and Distributed Computing 64, no. 12 (2004): 1399–413. http://dx.doi.org/10.1016/j.jpdc.2004.08.007.

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Trummer, Immanuel, Junxiong Wang, Ziyun Wei, et al. "SkinnerDB: Regret-bounded Query Evaluation via Reinforcement Learning." ACM Transactions on Database Systems 46, no. 3 (2021): 1–45. http://dx.doi.org/10.1145/3464389.

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SkinnerDB uses reinforcement learning for reliable join ordering, exploiting an adaptive processing engine with specialized join algorithms and data structures. It maintains no data statistics and uses no cost or cardinality models. Also, it uses no training workloads nor does it try to link the current query to seemingly similar queries in the past. Instead, it uses reinforcement learning to learn optimal join orders from scratch during the execution of the current query. To that purpose, it divides the execution of a query into many small time slices. Different join orders are tried in diffe

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45

Baranovskii, Evgenii S., and Mikhail A. Artemov. "Existence of Optimal Control for a Nonlinear-Viscous Fluid Model." International Journal of Differential Equations 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/9428128.

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We consider the optimal control problem for a mathematical model describing steady flows of a nonlinear-viscous incompressible fluid in a bounded three-dimensional (or a two-dimensional) domain with impermeable solid walls. The control parameter is the surface force at a given part of the flow domain boundary. For a given bounded set of admissible controls, we construct generalized (weak) solutions that minimize a given cost functional.

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46

Yao, Yuangen, Lijian Yang, Canjun Wang, et al. "Subthreshold Periodic Signal Detection by Bounded Noise-Induced Resonance in the FitzHugh–Nagumo Neuron." Complexity 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/5632650.

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Neurons can detect weak target signals from complex background signals through stochastic resonance (SR) and vibrational resonance (VR) mechanisms. However, random phase variation of rapidly fluctuating background signals is generally ignored in classical VR or SR studies. Here, the rapidly fluctuating background signals are modeled by bounded noise with random rapidly fluctuating phase derived from Wiener process. Then, the influences of bounded noise on the weak signal detection are discussed in the FitzHugh–Nagumo (FHN) neuron. Numerical results reveal the occurrence of bounded noise-induce

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47

Cavazos-Cadena, Rolando, and Emmanuel Fernández-Gaucherand. "Value iteration in a class of average controlled Markov chains with unbounded costs: necessary and sufficient conditions for pointwise convergence." Journal of Applied Probability 33, no. 04 (1996): 986–1002. http://dx.doi.org/10.1017/s0021900200100427.

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This work concerns controlled Markov chains with denumerable state space, (possibly)unboundedcost function, and an expectedaveragecost criterion. Under aLyapunov function condition, together with mild continuity-compactness assumptions, a simplenecessary and sufficientcriterion is given so that the relative value functions and differential costs produced by thevalue iterationscheme converge pointwise to the solution of the optimality equation; this criterion is applied to obtain convergence results when the cost function is bounded below or bounded above.

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Medvedev, Ilya N. "Universal modification of vector weighted method of correlated sampling with finite computational cost." Russian Journal of Numerical Analysis and Mathematical Modelling 34, no. 1 (2019): 43–55. http://dx.doi.org/10.1515/rnam-2019-0004.

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Abstract The weighted method of dependent trials or weighted method of correlated sampling (MCS) allows one to construct estimators for functionals based on the same Markov chain simultaneously for a given range of the problem parameters. Choosing an appropriate Markov chain, it is necessary to take into account additional conditions providing the finiteness of the computational cost of weighted MCS. In this paper we study the issue of finite computational cost of the method of correlated sampling (MCS) in application to evaluation of linear functionals of solutions to a set of systems of 2nd

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Shperberg, Shahaf, Natalie Morad, Lior Siag, Ariel Felner, and Dor Atzmon. "Bidirectional Bounded-Suboptimal Heuristic Search with Consistent Heuristics (Extended Abstract)." Proceedings of the International Symposium on Combinatorial Search 18 (July 20, 2025): 265–66. https://doi.org/10.1609/socs.v18i1.36011.

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Recent advancements in bidirectional heuristic search have yielded significant theoretical insights and novel algorithms. While most previous work has concentrated on optimal search methods, this paper focuses on bounded-suboptimal bidirectional search, where a bound on the suboptimality of the solution cost is specified. We build upon the state-of-the-art optimal bidirectional search algorithm, BAE*, designed for consistent heuristics, and introduce several variants of BAE* specifically tailored for the bounded-suboptimal context. Through experimental evaluation, we compare the performance of

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ALBERT, ELVIRA, MIQUEL BOFILL, CRISTINA BORRALLERAS, ENRIQUE MARTIN-MARTIN, and ALBERT RUBIO. "Resource Analysis driven by (Conditional) Termination Proofs." Theory and Practice of Logic Programming 19, no. 5-6 (2019): 722–39. http://dx.doi.org/10.1017/s1471068419000152.

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AbstractWhen programs feature a complex control flow, existing techniques for resource analysis produce cost relation systems (CRS) whose cost functions retain the complex flow of the program and, consequently, might not be solvable into closed-form upper bounds. This paper presents a novel approach to resource analysis that is driven by the result of a termination analysis. The fundamental idea is that the termination proof encapsulates the flows of the program which are relevant for the cost computation so that, by driving the generation of the CRS using the termination proof, we produce a l

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