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Simple Policies for Dynamic Pricing with Imperfect Forecasts

OPERATIONS RESEARCH 2013年第3期61卷 612-624页

作者： Chen, Yiwei Farias, Vivek F. Renmin Univ China Sch Business Beijing 100872 Peoples R China MIT Alfred P Sloan Sch Management Cambridge MA 02139 USA

We consider the "classical" single-product dynamic pricing problem allowing the "scale" of demand intensity to be modulated by an exogenous "market size" stochastic process. This is a natural model of dynamically changing market conditions. We show that for a broad family of Gaussian market-size processes, simple dynamic pricing rules that are essentially agnostic to the specification of this market-size process perform provably well. The pricing policies we develop are shown to compensate for forecast imperfections (or a lack of forecast information altogether) by frequent reoptimization and reestimation of the "instantaneous" market size.

关键词： optimal control dynamic programming suboptimal algorithms analysis of algorithms

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Energy-efficient user grouping algorithms for power minimisation in multi-carrier code division multiple access systems

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IET COMMUNICATIONS 2011年第18期5卷 2640-2647页

作者： Phasouliotis, A. So, D. K. C. Prawatmuang, W. Univ Manchester Sch Elect & Elect Engn Manchester Lancs England

Energy efficiency has become increasingly important in wireless communications nowadays. Saving energy will not only reduce operating cost but also reduces greenhouse gas emissions, which is important for combating climate change. The authors propose energy-efficient user grouping algorithms to provide power minimisation of grouped multi-carrier code division multiple access (MC-CDMA) and space-time block coding MC-CDMA systems in a cellular environment. Depending on the channel fading conditions, power control is utilised to minimise the total transmitted power under a bit error rate constraint. When the allocation is performed without a fair data rate requirement, the authors provide the optimal solution to the minimisation problem. However, when some fairness is considered, the optimal solution requires high computational complexity. Thus, the authors solve the problem by proposing two suboptimal algorithms. Simulation results illustrate a significantly reduced power consumption in comparison with other techniques.

关键词： minimisation problem power control radiocommunication minimisation optimal solution operating cost Optimisation techniques channel fading conditions bit error rate constraint energy-efficient user grouping algorithms error statistics Codes suboptimal algorithms climate change fading channels code division multiple access energy conservation energy efficiency grouped multicarrier code division multiple access Multiple access communication power consumption wireless communications space-time block coding MC-CDMA systems greenhouse gas emissions transmitted power multicarrier code division multiple access systems cellular environment fair data rate requirement space-time block codes computational complexity power minimisation Radio links and equipment Other topics in statistics

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Maximum commonality problems: Applications and analysis

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MANAGEMENT SCIENCE 2008年第1期54卷 194-207页

作者： Dawande, Milind Kumar, Subodha Mookerjee, Vijay Sriskandarajah, Chelliah Univ Texas Dallas Sch Management Richardson TX 75083 USA Univ Washington Michael G Foster Sch Business Seattle WA 98195 USA

Recently, an agile software development technique called extreme programming has caught the attention of practitioners and researchers in the software industry. A core practice of extreme programming is pair programming, where two developers work on the same piece of code. We introduce the problem of assigning pairs of developers to modules so as to maximize the commonality -a measure of the extent to which common developers work on related modules -subject to a load-balancing constraint that is motivated by the need to control the completion time of the project. We consider two variants of this problem. In MCAP(n), a developer is teamed up with exactly one other developer to form a pair that works together for the entire duration of the project. In MCAP(s), we allow a developer to pair with more than one other developer during the project. This "pair-splitting" version of the problem facilitates knowledge dissemination among developers, but can increase the effort needed for a developer to adjust to the work habits of several partners. The difference between the commonality achieved with and without pair splitting crucially depends on the underlying structure of the problem. For trees, we show that the value of the maximum commonality is the same for both MCAPn and MCAPs. Additionally, we obtain polynomial-time algorithms for both of these variants. For general graphs, both problems MCAPn and MCAPs are shown to be strongly NP-complete. We prove that the maximum commonality for MCAPs is at most 3 2 times the maximum commonality of MCAPn. We also provide polynomial-time algorithms and approximation results for a number of special cases of these problems.

关键词： analysis of algorithms computational complexity integer programming applications suboptimal algorithms

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Guided local search for the three-dimensional bin-packing problem

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INFORMS JOURNAL ON COMPUTING 2003年第3期15卷 267-283页

作者： Faroe, O Pisinger, D Zachariasen, M Univ Copenhagen Dept Comp Sci DK-2100 Copenhagen O Denmark

The three-dimensional bin-packing problem is the problem of orthogonally packing a set of boxes into a minimum number of three-dimensional bins. In this paper we present a heuristic algorithm based on guided local search. Starting with an upper bound on the number of bins obtained by a greedy heuristic, the presented algorithm iteratively decreases the number of bins, each time searching for a feasible packing of the boxes. The process terminates when a given time limit has been reached or the upper bound matches a pre-computed lower bound. The algorithm can also be applied to two-dimensional bin-packing problems by having a constant depth for all boxes and bins. Computational experiments are reported for two- and three-dimensional instances with up to 200 boxes, showing that the algorithm on average finds-better solutions than do heuristics from the literature.

关键词： analysis of algorithms suboptimal algorithms cutting and packing

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Update with out-of-sequence measurements in tracking: Exact solution

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2002年第3期38卷 769-778页

作者： Bar-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA

In target tracking systems measurements are typically collected in "scans" or "frames" and then they are transmitted to a processing center. In multisensor tracking systems that operate in a centralized manner, there are usually different time delays in transmitting the scans or frames from the various sensors to the center. This can lead to situations where measurements from the same target arrive out of sequence. Such "out-of-sequence" measurement (OOSM) arrivals can occur even in the absence of scan/frame communication time delays. The resulting "negative-time measurement update" problem, which is quite common in real multisensor systems, was solved previously only approximately in the literature. The exact state update equation, for such a problem is presented. The optimal and two suboptimal algorithms are compared on a number of realistic examples, including a GMTI (ground moving target indicator) radar case.

关键词： delays radar tracking sensor fusion target tracking GMTI radar ground moving target indicator multisensor tracking systems negative-time measurement update problem optimal algorithms out-of-sequence measurements suboptimal algorithms target tracking syst Multisensor systems Optimization algorithms Sensor fusion Moving target detector radar target tracking Target tracking delay

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Integrating interval estimates of global optima and local search methods for combinatorial optimization problems

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JOURNAL OF HEURISTICS 2000年第4期6卷 481-500页

作者： Ovacik, IM Rajagopalan, S Uzsoy, R i2 Technol Irving TX 75039 USA Purdue Univ Sch Ind Engn W Lafayette IN 47907 USA

The problem of estimating the global optimal values of intractable combinatorial optimization problems is of interest to researchers developing and evaluating heuristics for these problems. In this paper we present a method for combining statistical optimum prediction techniques with local search methods such as simulated annealing and tabu search and illustrate the approach on a single machine scheduling problem. Computational experiments show that the approach yields useful estimates of optimal values with very reasonable computational effort.

关键词： programming heuristic analysis of algorithms suboptimal algorithms sequencing deterministic single machine

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A 1.47-approximation algorithm for a preemptive single-machine scheduling problem

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OPERATIONS RESEARCH LETTERS 2000年第4期26卷 149-154页

作者： Goemans, MX Wein, JM Williamson, DP IBM Corp Thomas J Watson Res Ctr Yorktown Heights NY 10598 USA MIT Cambridge MA 02139 USA Polytech Univ MetroTech Ctr 5 Dept Comp Sci Brooklyn NY 11201 USA

In this note, we give a 1.47-approximation algorithm for the preemptive scheduling of jobs with release dates on a single machine so as to minimize the weighted sum of job completion times;this problem is denoted by 1\r(j), pmtn\ Sigma(j)w(j)C(j) in the notation of Lawler et al. (Handbooks in Operations Research and Management Science, Vol. 4, Logistics of Production and Inventory, North-Holland, Amsterdam, pp. 445-522). Our result improves on a 2-approximation algorithm due to Hall et al. Math. Oper. Res. 22 (1997) 513-544, and also yields an improved bound on the quality of a well-known linear programming relaxation of the problem. (C) 2000 Elsevier Science B.V. All rights reserved.

关键词： analysis of algorithms suboptimal algorithms production/scheduling approximations/heuristic production/scheduling single-machine deterministic scheduling

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A 5/3 approximation algorithm for the clustered traveling salesman tour and path problems

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OPERATIONS RESEARCH LETTERS 1999年第1-2期24卷 29-35页

作者： Anily, S Bramel, J Hertz, A Columbia Univ Grad Sch Business New York NY 10027 USA Tel Aviv Univ Fac Management IL-69978 Tel Aviv Israel Ecole Polytech Fed Lausanne Dept Math Lausanne Switzerland

We consider the ordered cluster traveling salesman problem (OCTSP). In this problem, a vehicle starting and ending at a given depot must visit a set of n points. The points are partitioned into K, K less than or equal to n, prespecified clusters. The vehicle must first visit the points in cluster 1, then the points in cluster 2,..., and finally the points in cluster K so that the distance traveled is minimized. We present a 5/3-approximation algorithm for this problem which runs in O(n(3)) time. We show that our algorithm can also be applied to the path version of the OCTSP: the ordered cluster traveling salesman path problem (OCTSPP). Here the (different) starting and ending points of the vehicle may or may not be prespecified. For this problem, our algorithm is also a 5/3-approximation algorithm. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： analysis of algorithms suboptimal algorithms transportation vehicle routing

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Edge coloring a k‐tree into two smaller trees

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Networks 1998年第4期29卷

作者： Dilip Chhajed Department of Business Administration University of Illinois at Urbana‐Champaign 350 Commerce West Building Champaign Illinois 61820

The problem of the edge coloring partial k ‐tree into two partial p ‐ and q ‐trees with p , q < k is considered. An algorithm is provided to construct such a coloring with p + q = k . Usefulness of this result in a Lagrangian decomposition framework to solve certain combinatorial optimization problems is discussed. ® 1997 John Wiley & Sons, Inc.

关键词： networks/graphs theory facilities planning location analysis of algorithms suboptimal algorithms

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An integrated approach for modeling and solving the general multiprocessor job-shop scheduling problem using tabu search

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ANNALS OF OPERATIONS RESEARCH 1997年第s期70卷 281-306页

作者： DauzerePeres, S Paulli, J ECOLE MINES DEPT AUTOMAT CONTROL & PROD ENGN F-44070 NANTES 03 FRANCE AARHUS UNIV DEPT OPERAT RES DK-8000 AARHUS C DENMARK

The problem considered in this paper is an important extension of the classical job-shop scheduling problem, where the same operation can be performed on more than one machine. The problem is to assign each operation to a machine and to sequence the operations on the machines, such that the makespan of a set of jobs is minimized. We introduce an extended version of the disjunctive graph model, that is able to take into account the fact that operations have to be assigned to machines. This allows us to present an integrated approach, by defining a neighborhood structure for the problem where there is no distinction between reassigning or resequencing an operation. This neighborhood is proved to be connected. A tabu search procedure is proposed and computational results are provided.

关键词： analysis of algorithms suboptimal algorithms tabu search production/scheduling sequencing deterministic multiple machine multiprocessor job-shop scheduling disjunctive graph model

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