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On semidefinite descriptions for convex hulls of quadratic programs Operations Research Letters (IF 1.1) Pub Date : 2024-03-07 Alex L. Wang, Fatma Kılınç-Karzan
Quadratically constrained quadratic programs (QCQPs) are a highly expressive class of nonconvex optimization problems. While QCQPs are NP-hard in general, they admit a natural convex relaxation via the standard semidefinite program (SDP) relaxation. In this paper we study when the convex hull of the epigraph of a QCQP coincides with the projected epigraph of the SDP relaxation. We present a sufficient
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How many clues to give? A bilevel formulation for the minimum Sudoku clue problem Operations Research Letters (IF 1.1) Pub Date : 2024-03-07 Gennesaret Tjusila, Mathieu Besançon, Mark Turner, Thorsten Koch
It has been shown that any 9 by 9 Sudoku puzzle must contain at least 17 clues to have a unique solution. This paper investigates the more specific question: given a particular completed Sudoku grid, what is the minimum number of clues in any puzzle whose unique solution is the given grid? We call this problem the Minimum Sudoku Clue Problem (MSCP). We formulate MSCP as a binary bilevel linear program
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Faster algorithm and sharper analysis for constrained Markov decision process Operations Research Letters (IF 1.1) Pub Date : 2024-03-06 Tianjiao Li, Ziwei Guan, Shaofeng Zou, Tengyu Xu, Yingbin Liang, Guanghui Lan
The problem of constrained Markov decision process (CMDP) is investigated, where an agent aims to maximize the expected accumulated reward subject to constraints on its utilities/costs. We propose a new primal-dual approach with a novel integration of entropy regularization and Nesterov's accelerated gradient method. The proposed approach is shown to converge to the global optimum with a complexity
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On Upper Bounds for the Multiple Knapsack Assignment Problem Operations Research Letters (IF 1.1) Pub Date : 2024-03-06 Laura Galli, Adam N. Letchford
The is a strongly -hard combinatorial optimisation problem, with several applications. We show that an for the problem, due to Kataoka and Yamada, can be computed in linear time. We then show that some bounds due to Martello and Monaci dominate the Kataoka-Yamada bound. Finally, we define an even stronger bound, which turns out to be particularly effective when the number of knapsacks is not a multiple
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Envy-free house allocation with minimum subsidy Operations Research Letters (IF 1.1) Pub Date : 2024-03-02 Davin Choo, Yan Hao Ling, Warut Suksompong, Nicholas Teh, Jian Zhang
House allocation refers to the problem where houses are to be allocated to agents so that each agent receives one house. Since an envy-free house allocation does not always exist, we consider finding such an allocation in the presence of subsidy. We show that computing an envy-free allocation with minimum subsidy is NP-hard in general, but can be done efficiently if differs from by an additive constant
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Markov decision process design: A framework for integrating strategic and operational decisions Operations Research Letters (IF 1.1) Pub Date : 2024-02-21 Seth Brown, Saumya Sinha, Andrew J. Schaefer
We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates the design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively. We seek to simultaneously minimize the design costs and the subsequent expected operational costs.
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Scalar representations and Hausdorff continuity of solution mappings to parametric set optimization problems via set less order relations Operations Research Letters (IF 1.1) Pub Date : 2024-01-26 Lam Quoc Anh, Pham Thanh Duoc, Ha Manh Linh
This paper aims to formulate scalar representations and stability conditions for parametric set optimization problems involving set less order relations. We first introduce new nonlinear scalarization functions for sets and discuss their properties, and then they are utilized to establish scalar representations for solutions to such problems. Finally, we study sufficient conditions for the Hausdorff
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Incentive-compatible cost allocations for inventory games with private information Operations Research Letters (IF 1.1) Pub Date : 2024-01-27 Yinlian Zeng, Siyi Wang, Xiaoqiang Cai, Lianmin Zhang
In this paper we design cost allocation rules for inventory games with private information. First, we design incentive-compatible cost allocation rules for inventory games with private information via Vickrey-Clarke-Groves (VCG) rules. Then, we propose incentive-compatible and approximate budget-balanced cost allocations via polynomial approximations such as the Chebyshev approximation and the Taylor
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A combined variable aggregation presolving technique for mixed integer programming Operations Research Letters (IF 1.1) Pub Date : 2024-01-26 Houshan Zhang, Jianhua Yuan
Presolving is a critical component in modern mixed integer programming (MIP ) solvers. In this paper, we propose a new and effective presolving method named inequation-based variable aggregation and develop a combined variable aggregation (VA ) technique with the advantage of significantly reducing the scales of MIP problems. This technique is particularly effective for problems involving semi-continuous
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A novel stepsize for gradient descent method Operations Research Letters (IF 1.1) Pub Date : 2024-01-24 Pham Thi Hoai, Nguyen The Vinh, Nguyen Phung Hai Chung
We propose a novel adaptive stepsize for the gradient descent scheme to solve unconstrained nonlinear optimization problems. With the convex and smooth objective satisfying locally Lipschitz gradient we obtain the complexity O(1k) of f(xk)−f⁎ at most. By using the idea of the new stepsize, we propose another new algorithm based on the projected gradient for solving a class of nonconvex optimization
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Strategic inattention of multi-product firms with free entry Operations Research Letters (IF 1.1) Pub Date : 2024-01-17 Lijun Pan
This paper considers the strategic (in)attention of multi-product firms with endogenous product range choice and introduces free entry prior to firms' strategic choices on attention or inattention. We find that within-firm cannibalization of multi-product firms plays a key role in determining firms' strategic behavior. Furthermore, with free entry, we identify a single threshold that determines whether
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Bounds on revenue for the random consideration set choice model Operations Research Letters (IF 1.1) Pub Date : 2024-01-18 Wentao Lu
The random consideration set choice model is a recently proposed choice model that can capture the stochastic choice behavior of consumers. One advantage of the random consideration set choice model is that it can accommodate some phenomena that cannot be explained by the multinomial logit model. In this paper, we prove revenue bounds when the attention probabilities and preference order over products
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Max cut and semidefinite rank Operations Research Letters (IF 1.1) Pub Date : 2024-01-17 Renee Mirka, David P. Williamson
This paper considers the relationship between semidefinite programs (SDPs), matrix rank, and maximum cuts of graphs. Utilizing complementary slackness conditions for SDPs, we investigate when the rank 1 feasible solution corresponding to a max cut is the unique optimal solution to the Goemans-Williamson max cut SDP by showing the existence of an optimal dual solution with rank n−1. Our results consider
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Must pollution abatement harm the supplier in a multi-echelon supply chain? Operations Research Letters (IF 1.1) Pub Date : 2024-01-17 Ismail Saglam
This paper studies the welfare effects of the abatement cost burden of a supplier in a multi-echelon supply chain. We theoretically show that the profits of all echelons other than the supplier become lower when the supplier contributes more to the abatement. Also, we computationally show that the profit of the supplier may be higher when it makes a small amount of contribution to the abatement provided
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Demand information sharing in Cournot-Bertrand model Operations Research Letters (IF 1.1) Pub Date : 2024-01-17 Abdul Quadir
We consider a Cournot-Bertrand competition with uncertain demand where firms receive private information about it. We prove that sharing information is a dominant strategy for the quantity-setting firm and not sharing is a dominant strategy for the price-setting firm. We uncover that the quantity-setting firm enjoys higher expected profits with more precise information and pools the information, whereas
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A quadratic-order problem kernel for the traveling salesman problem parameterized by the vertex cover number Operations Research Letters (IF 1.1) Pub Date : 2024-01-12 René van Bevern, Daniel A. Skachkov
The NP-hard graphical traveling salesman problem (GTSP) is to find a closed walk of total minimum weight that visits each vertex in an undirected edge-weighted and not necessarily complete graph. We present a problem kernel with τ2+τ vertices for GTSP, where τ is the vertex cover number of the input graph. Any α-approximate solution for the problem kernel also gives an α-approximate solution for the
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Universally optimal staffing of Erlang-A queues facing uncertain arrival rates Operations Research Letters (IF 1.1) Pub Date : 2023-12-29 Yaşar Levent Koçağa
In many service systems, the staffing decisions must be made before the arrival rate is known with certainty. Thus, it is more appropriate to consider the arrival rate as a random variable at the time of the staffing decision. Motivated by this observation, we study the staffing problem in a service system modeled as an Erlang-A queue facing a random arrival rate. For linear staffing costs, linear
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An inexact algorithm for stochastic variational inequalities Operations Research Letters (IF 1.1) Pub Date : 2023-12-28 Emelin L. Buscaglia, Pablo A. Lotito, Lisandro A. Parente
We present a new Progressive Hedging Algorithm to solve Stochastic Variational Inequalities in the formulation introduced by Rockafellar and Wets in 2017, allowing the generated subproblems to be approximately solved with an implementable tolerance condition. Our scheme is based on Hybrid Inexact Proximal Point methods and generalizes the exact algorithm developed by Rockafellar and Sun in 2019, providing
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On Gaussian Markov processes and Polya processes Operations Research Letters (IF 1.1) Pub Date : 2023-12-28 Kerry Fendick, Ward Whitt
In previous work we characterized Gaussian Markov processes with stationary increments and showed that they arise as asymptotic approximations for stochastic point processes with a random rate such as Polya processes, which can be useful to model over-dispersion and path-dependent behavior in service system arrival processes. Here we provide additional insight into these stochastic processes.
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Diffusion approximation of a special bandwidth sharing model via infinitesimal generators with a lifting-projection method Operations Research Letters (IF 1.1) Pub Date : 2023-12-28 Bowen Xie, Yijin Gao
We consider a proposed unsolved conjecture of a special bandwidth-sharing model integrating streamings and file transfers as initiated in Kumar and Massoulié (2007). Using the infinitesimal generator approach, we demonstrate its diffusion approximation with a special time-scale separation parameter. To this end, we introduce a lifting-projection method, and exhibit a novel function to show the generator
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A note on quadratic constraints with indicator variables: Convex hull description and perspective relaxation Operations Research Letters (IF 1.1) Pub Date : 2023-12-21 Andrés Gómez, Weijun Xie
In this paper, we study the mixed-integer nonlinear set given by a separable quadratic constraint on continuous variables, where each continuous variable is controlled by an additional indicator. This set occurs pervasively in optimization problems with uncertainty and in machine learning. We show that optimization over this set is NP-hard. Despite this negative result, we discover links between the
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On truthful constrained heterogeneous facility location with max-variant cost Operations Research Letters (IF 1.1) Pub Date : 2023-12-20 Mohammad Lotfi, Alexandros A. Voudouris
We consider a problem where agents have private positions on a line, and public approval preferences over two facilities, and their cost is the maximum distance from their approved facilities. The goal is to decide the facility locations to minimize the total and the max cost, while incentivizing the agents to be truthful. We design a strategyproof mechanism that is simultaneously 11- and 5-approximate
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On computing sparse generalized inverses Operations Research Letters (IF 1.1) Pub Date : 2023-12-15 Gabriel Ponte, Marcia Fampa, Jon Lee, Luze Xu
The M-P (Moore-Penrose) pseudoinverse is used in several linear-algebra applications. It is convenient to construct sparse block-structured matrices satisfying some relevant properties of the M-P pseudoinverse for specific applications. Aiming at row-sparse generalized inverses, we consider 2,1-norm minimization (and generalizations). We show that a 2,1-norm minimizing generalized inverse satisfies
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Partially egalitarian portfolio selection Operations Research Letters (IF 1.1) Pub Date : 2023-12-07 Yiming Peng, Vadim Linetsky
We propose a new portfolio optimization framework, partially egalitarian portfolio selection (PEPS). Inspired by the celebrated LASSO regression and its recent variant partially egalitarian LASSO (PELASSO) developed in [1] in the context of the forecast combinations problem in econometrics in [1], we regularize the mean-variance portfolio optimization of Markowitz by adding two regularizing terms that
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The complexity of geometric scaling Operations Research Letters (IF 1.1) Pub Date : 2023-12-02 Antoine Deza, Sebastian Pokutta, Lionel Pournin
Geometric scaling, introduced by Schulz and Weismantel in 2002, solves the integer optimization problem max{c⋅x:x∈P∩Zn} by means of primal augmentations, where P⊂Rn is a polytope. We restrict ourselves to the important case when P is a 0/1-polytope. Schulz and Weismantel showed that no more than O(nlog2n‖c‖∞) calls to an augmentation oracle are required. This upper bound can be improved to O(nlog2‖c‖∞)
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A note on clustering aggregation for binary clusterings Operations Research Letters (IF 1.1) Pub Date : 2023-11-27 Jiehua Chen, Danny Hermelin, Manuel Sorge
We consider the clustering aggregation problem in which we are given a set of clusterings and want to find an aggregated clustering which minimizes the sum of mismatches to the input clusterings. In the binary case (each clustering is a bipartition) this problem was known to be NP-hard under Turing reductions. We strengthen this result by providing a polynomial-time many-one reduction. Our result also
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Towards optimal running timesfor optimal transport Operations Research Letters (IF 1.1) Pub Date : 2023-11-24 Jose Blanchet, Arun Jambulapati, Carson Kent, Aaron Sidford
We provide faster algorithms for approximating the optimal transport distance, e.g. earth mover's distance, between two discrete probability distributions on n elements. We present two algorithms which compute couplings between marginal distributions with an expected transportation cost that is within an additive ϵ of optimal in time O˜(n2/ϵ); one algorithm is straightforward to parallelize and implementable
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On the dimension of the set of yolk centers Operations Research Letters (IF 1.1) Pub Date : 2023-11-20 James P. Bailey
The yolk describes likely outcomes in the spatial model of voting. Martin, Nganmeni, and Tovey conjectured that given an odd number of ideal points in Rk the dimension of the set of yolk centers is at most k−2. We prove this conjecture and show the result is tight. We also show that k−1 is tight for an even of number voters. Moreover, our results provide some insight into whether uniqueness is a general
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Semidefinite representable reformulations for two variants of the trust-region subproblem Operations Research Letters (IF 1.1) Pub Date : 2023-11-17 Sarah Kelly, Yuyuan Ouyang, Boshi Yang
Motivated by encouraging numerical results in Eltved and Burer (2023) [13], in this note we consider two specific variants of the trust-region subproblem and provide exact semidefinite representable reformulations. The first is over the intersection of two balls; the second is over the intersection of a ball and a special second-order conic representable set. Different from the technique developed
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Comparing perspective reformulations for piecewise-convex optimization Operations Research Letters (IF 1.1) Pub Date : 2023-11-14 Renan Spencer Trindade, Claudia D'Ambrosio, Antonio Frangioni, Claudio Gentile
We aim at generalizing formulations for non-convex piecewise-linear problems to mathematical programs whose non-convexities are only expressed in terms of piecewise-convex univariate functions. This is motivated by solving Mixed-Integer Non-Linear Programming (MINLP) problems with separable non-convex functions via the Sequential Convex MINLP technique. We theoretically and computationally compare
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Efficient recursion-quadrature algorithms for pricing Asian options and variance derivatives under stochastic volatility and Lévy jumps Operations Research Letters (IF 1.1) Pub Date : 2023-11-14 Weinan Zhang, Pingping Zeng, Yue Kuen Kwok
We propose efficient algorithms for pricing discretely monitored arithmetic Asian options and variance derivatives, which utilize the recursion of characteristic functions, quadrature over the variance/activity rate dimension, and frame projection method of approximating the density function of the log-asset price. The classes of dynamic asset price models include the stochastic volatility models with
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Communication-aware scheduling of precedence-constrained tasks on related machines Operations Research Letters (IF 1.1) Pub Date : 2023-11-13 Yu Su, Shai Vardi, Xiaoqi Ren, Adam Wierman
Scheduling precedence-constrained tasks is a classical problem that has been studied for more than fifty years. However, little progress has been made in the setting where there are non-uniform communication delays between tasks. In this work, we propose a new scheduler, Generalized Earliest Time First (GETF), and provide the first provable, worst-case approximation guarantees for the goals of minimizing
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A random arrival rule for airport problems with fuzzy costs Operations Research Letters (IF 1.1) Pub Date : 2023-11-07 H. Galindo, J.M. Gallardo, A. Jiménez-Losada
Airport games model situations in which a group of agents use a common facility and they are ordered according to the cost associated with the use that each one of them make of that facility. In this paper we assumed that the cost of the common project is precise but the individual costs are modeled using fuzzy numbers. Our goal will be to obtain a precise allocation of the cost of the common facility
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On the softplus penalty for large-scale convex optimization Operations Research Letters (IF 1.1) Pub Date : 2023-11-07 Meng Li, Paul Grigas, Alper Atamtürk
We study a penalty reformulation of constrained convex optimization based on the softplus penalty function. For strongly convex objectives, we develop upper bounds on the objective value gap and the violation of constraints for the solutions to the penalty reformulations by analyzing the solution path of the reformulation with respect to the smoothness parameter. We use these upper bounds to analyze
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WaveCorr: Deep reinforcement learning with permutation invariant convolutional policy networks for portfolio management Operations Research Letters (IF 1.1) Pub Date : 2023-11-04 Saeed Marzban, Erick Delage, Jonathan Yu-Meng Li, Jeremie Desgagne-Bouchard, Carl Dussault
We present a new portfolio policy convolutional neural network architecture, WaveCorr, for deep reinforcement learning applied to portfolio optimization. WaveCorr is the first to treat asset correlation while preserving “asset invariance property”, a new permutation invariance property that significantly increases the stability of performance in problems where input indexing is done arbitrarily. A
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Coalition structure value considering the outside alignment option of priori coalition Operations Research Letters (IF 1.1) Pub Date : 2023-10-31 Xiaohui Yu, Qiang Zhang, Yingying Gao, Chenglin Wang
In a cooperative game with a coalition structure (i.e., coalition structure game), a coalition structure value (CS-value) is obtained on the assumption that the coalition structure has been or can be formed. The necessity analysis of coalition formation is easy to be ignored in the CS-values, such as the Owen value. In this paper, the alignment probability of other coalitions out of a priori coalition
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Multi-product pricing: A discrete choice model based on Markov Chain Choice Model combined with reservation prices Operations Research Letters (IF 1.1) Pub Date : 2023-10-31 Laura Sprenkels, Zümbül Atan, Ivo Adan
Finding the optimal selling prices for an assortment of multiple, substitutable products is a problem that occurs daily in many industries. To solve this problem, a new customer choice model is proposed, based on the Markov Chain Choice Model combined with reservation prices. A discrete version of the model is proposed and it is solved to optimality. This discrete model is instrumental in a simulation
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Fairness and efficiency of the random serial dictatorship on preference domains with a tier structure Operations Research Letters (IF 1.1) Pub Date : 2023-10-23 Yajing Chen, Zhenhua Jiao, Wen Qin, Jinghong Shan
In this note, we study the envy-freeness and ordinal efficiency of the random serial dictatorship (RSD) rule on preference domains with a tier structure. Specifically, we obtain that the RSD rule is envy-free on restricted tier preference domains. For the ordinal efficiency axiom, we show that the almost-singleton condition is not sufficient for the RSD rule to be ordinally efficient. For assignment
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Reducibility bounds of objective functions over the integers Operations Research Letters (IF 1.1) Pub Date : 2023-10-16 Friedrich Eisenbrand, Christoph Hunkenschröder, Kim-Manuel Klein, Martin Koutecký, Asaf Levin, Shmuel Onn
We study the settings where we are given a separable objective function of n variables defined in a given box of integers. We show that in many cases we can replace the given objective function by a new function with a much smaller domain. Our results apply to linear functions as well as to nonlinear separable convex objective functions.
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A blessing in disguise: Collusion equivalent phenomenon under environmental regulation Operations Research Letters (IF 1.1) Pub Date : 2023-10-17 Zhongqi Deng, Xuecheng Fan, Tingfan Gao
This study has revealed an intriguing discovery: environmental regulation could bring unexpected profits to both environmentally responsible and polluting firms. While enabling regulated firms to shift some regulatory costs onto consumers, environmental regulation can still achieve a Pareto improvement when the regulatory intensity is appropriate.
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Mixed-strategy equilibrium of the symmetric production in advance game: The missing case Operations Research Letters (IF 1.1) Pub Date : 2023-10-17 Attila Tasnádi
The mixed-strategy equilibrium of the symmetric production-in-advance type capacity-constrained Bertrand-Edgeworth duopoly game has not been derived analytically over the entire range of intermediate capacities in the literature. In this paper we derive for the missing region a symmetric mixed-strategy equilibrium analytically.
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Bilevel linear optimization belongs to NP and admits polynomial-size KKT-based reformulations Operations Research Letters (IF 1.1) Pub Date : 2023-10-14 Christoph Buchheim
It is a well-known result that bilevel linear optimization is NP-hard. In many publications, reformulations as mixed-integer linear optimization problems are proposed, which suggests that the decision version of the problem belongs to NP. However, to the best of our knowledge, a rigorous proof of membership in NP has never been published, so we close this gap by reporting a simple but not entirely
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Price of Anarchy with multiple information sources under competition Operations Research Letters (IF 1.1) Pub Date : 2023-10-12 Fernando Miguelez, Urtzi Ayesta, Josu Doncel
We characterize the Price of Anarchy (PoA) in a single channel under the presence of K competing sources. As performance metric we consider the Age of Information, which measures the freshness of information in a remote system. In our main results we show that when the service times of all sources are equal the PoA is 2−1K, and that otherwise the PoA is unbounded from above. Numerical computations
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Minimizing the effective graph resistance by adding links is NP-hard Operations Research Letters (IF 1.1) Pub Date : 2023-10-12 Robert E. Kooij, Massimo A. Achterberg
The effective graph resistance, also known as the Kirchhoff index, is metric that is used to quantify the robustness of a network. We show that the optimisation problem of minimizing the effective graph resistance of a graph by adding a fixed number of links, is NP-hard.
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An FPTAS for budgeted laminar matroid independent set Operations Research Letters (IF 1.1) Pub Date : 2023-10-12 Ilan Doron-Arad, Ariel Kulik, Hadas Shachnai
We study the budgeted laminar matroid independent set problem. The input is a ground set, where each element has a cost and a non-negative profit, along with a laminar matroid over the elements and a budget. The goal is to select a maximum profit independent set of the matroid whose total cost is bounded by the budget. We present a fully polynomial-time approximation scheme (FPTAS) for the problem
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Reciprocal degree distance and Hamiltonian properties of graphs Operations Research Letters (IF 1.1) Pub Date : 2023-10-11 Rajkaran Kori, Abhyendra Prasad, Ashish K. Upadhyay
For a connected graph G, the reciprocal degree distance (RDD) of the graph G is defined as; RDD(G)=∑u≠vdegG(u)+degG(v)dG(u,v), where degG(u) is the degree of u in G and dG(u,v) is the distance between u and v in G. In this article, we give sufficient condition for a graph to be traceable, Hamiltonian, Hamiltonian-connected in terms of RDD(G).
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Corrigendum to “A new axiomatization of the Shapley-solidarity value for games with a coalition structure” [Oper. Res. Lett. 46 (2018) 163–167] Operations Research Letters (IF 1.1) Pub Date : 2023-10-05 Tao Liu, Wenrong Lyu, Xun-Feng Hu, Erfang Shan
We provide a new basis for TU-games with any given coalition structure, serving as a corrigendum concerning the basis applied to characterize the Shapley-solidarity value, introduced by Hu and Li in [Oper. Res. Lett. 46 (2018) 163–167].
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On the duration of a gambler's ruin problem Operations Research Letters (IF 1.1) Pub Date : 2023-10-05 Sheldon M. Ross
Consider a gambler who on each bet either wins 1 with probability p or loses 1 with probability q=1−p, with the results of successive bets being independent. The gambler will stop betting when they are either up k or down k. Letting N be the number of bets made, we show that N is a new better than used random variable. Moreover, we show that if k is even then N/2 has an increasing failure rate, and
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On complexity of finding strong-weak solutions in bilevel linear programming Operations Research Letters (IF 1.1) Pub Date : 2023-10-04 Tomás Lagos, Oleg A. Prokopyev
We consider bilevel linear programs (BLPs) that model hierarchical decision-making settings with two independent decision-makers (DMs), referred to as a leader (an upper-level DM) and a follower (a lower-level DM). BLPs are strongly NP-hard. In general, the follower's rational reaction (i.e., a set that contains optimal solutions of the lower-level problem for a given leader's decision) is not a singleton
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Multiprocessor jobs, preemptive schedules, and one-competitive online algorithms Operations Research Letters (IF 1.1) Pub Date : 2023-10-04 Jiří Sgall, Gerhard J. Woeginger
We study online preemptive makespan minimization on m parallel machines, where multiprocessor jobs arrive over time and have widths (i.e., the number of machines used) from some fixed set W⊆{1,2,…,m}. For every number m of machines we concisely characterize all the sets W for which there exists a 1-competitive fully online algorithm and all the sets W for which there is a 1-competitive nearly online
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Lower bounds for American option prices with control variates Operations Research Letters (IF 1.1) Pub Date : 2023-09-26 François-Michel Boire, R. Mark Reesor, Lars Stentoft
This article discusses the application of optimally sampled control variates in the context of the Least-Squares Monte Carlo algorithm for pricing American options. We demonstrate theoretically that optimal sampling introduces bias when estimated exercise times are not stopping times. Numerical results show that this bias is an accurate proxy for the positive foresight bias of American option price
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A randomized algorithm for online metric b-matching Operations Research Letters (IF 1.1) Pub Date : 2023-09-25 Bala Kalyanasundaram, Kirk Pruhs, Cliff Stein
We give a randomized algorithm for online metric b-matching that is O(log2k) competitive, where k is the number of server locations, by giving a black box reduction from b-matching on a hierarchically separated tree to a uniform metric space.
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Robust integrated planning for LEO satellite network design and service operations Operations Research Letters (IF 1.1) Pub Date : 2023-09-19 Zeyu Zhang, Chao Zhang, Qiao-Chu He, Pinghui Wang
We try to understand Low Earth Orbit (LEO) satellites from an operations research perspective. We propose an integrated model to support the strategic designing of ground stations, as well as the operational planning of traffic routes. A Mixed-Integer Nonlinear Program is proposed to solve the integrated model. Through a case study using satellite simulation platforms, we find that the responsiveness
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Optimal switching policy for batch servers Operations Research Letters (IF 1.1) Pub Date : 2023-09-18 Yinbin Han, Zizhuo Wang
We consider a queueing system with two Poisson arrival queues and two batch servers with finite capacities within a pre-specified time horizon. The problem is to decide a switching time of the two servers in order to maximize the total expected number of customers served in the end. We propose an optimal time threshold-based switching policy and analyze the properties of the switching policy. We also
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Absorbing games with irrational values Operations Research Letters (IF 1.1) Pub Date : 2023-09-18 Miquel Oliu-Barton, Guillaume Vigeral
Many classes of two-player zero-sum stochastic games have the orderfield property; that is, if all payoffs and transitions belong to some field, so does the limit value. Is it also the case for absorbing games? No: In this note, we exhibit m×m absorbing games with rational data whose limit values are algebraic of degree m, for each m∈N⁎. Furthermore, we provide maximal conditions for the orderfield
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Online learning for route planning with on-time arrival reliability Operations Research Letters (IF 1.1) Pub Date : 2023-09-17 Hongyi Jiang, Samitha Samaranayake, Qing Zhao
Consider a network where travel times on edges are i.i.d. over T rounds with unknown distributions. One wishes to choose departure times and routes sequentially between a given origin-destination pair across T rounds to minimize the expectations of: 1) number of rounds when the travel time exceeds an upper bound, and 2) summation over all rounds of the square of the difference between the given target
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A practical multi-objective auction design and optimization framework for sponsored search Operations Research Letters (IF 1.1) Pub Date : 2023-09-17 Qian Li, Liang Wang, Lirong Xia, Wenxun Zheng, Yuxuan Zhou
We propose a simple, flexible, efficient, and general framework for running large-scale highly-dynamic sponsored search auctions. Our framework aims at exploring optimal tradeoffs among various objectives of three parties: platform, advertisers, and users. We model the optimal tradeoffs as an online linear program problem, which can be addressed by a simple approach based on semi-Lagrangian duality
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