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147
Combinatorial auctions: A survey
, 2000
"... Many auctions involve the sale of a variety of distinct assets. Examples are airport time slots, delivery routes and furniture. Because of complementarities (or substitution effects) between the different assets, bidders have preferences not just for particular items but for sets or bundles of items ..."
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Cited by 213 (1 self)
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Many auctions involve the sale of a variety of distinct assets. Examples are airport time slots, delivery routes and furniture. Because of complementarities (or substitution effects) between the different assets, bidders have preferences not just for particular items but for sets or bundles of items. For this reason, economic efficiency is enhanced if bidders are allowed to bid on bundles or combinations of different assets. This paper surveys the state of knowledge about the design of combinatorial auctions. Second, it uses this subject as a vehicle to convey the aspects of integer programming that are relevant for the
A Parallel Genetic Algorithm for the Set Partitioning Problem
, 1994
"... In this dissertation we report on our efforts to develop a parallel genetic algorithm and apply it to the solution of the set partitioning problema difficult combinatorial optimization problem used by many airlines as a mathematical model for flight crew scheduling. We developed a distributed stea ..."
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Cited by 81 (2 self)
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In this dissertation we report on our efforts to develop a parallel genetic algorithm and apply it to the solution of the set partitioning problema difficult combinatorial optimization problem used by many airlines as a mathematical model for flight crew scheduling. We developed a distributed steadystate genetic algorithm in conjunction with a specialized local search heuristic for solving the set partitioning problem. The genetic algorithm is based on an island model where multiple independent subpopulations each run a steadystate genetic algorithm on their own subpopulation and occasionally fit strings migrate between the subpopulations. Tests on forty realworld set partitioning problems were carried out on up to 128 nodes of an IBM SP1 parallel computer. We found that performance, as measured by the quality of the solution found and the iteration on which it was found, improved as additional subpopulations were added to the computation. With larger numbers of subpopulations the genetic algorithm was regularly able to find the optimal solution to problems having up to a few thousand integer variables. In two cases, highquality integer feasible solutions were found for problems with 36,699 and 43,749 integer variables, respectively. A notable limitation we found was the difficulty solving problems with many constraints.
Clearing algorithms for barter exchange markets: Enabling nationwide kidney exchanges
 In Proceedings of the 8th ACM Conference on Electronic commerce (EC
, 2007
"... In barterexchange markets, agents seek to swap their items with one another. These swaps consist of cycles of agents, with each agent receiving the item of the next agent in the cycle. We focus mainly on the upcoming national kidneyexchange market, where patients with kidney disease can obtain com ..."
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Cited by 74 (7 self)
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In barterexchange markets, agents seek to swap their items with one another. These swaps consist of cycles of agents, with each agent receiving the item of the next agent in the cycle. We focus mainly on the upcoming national kidneyexchange market, where patients with kidney disease can obtain compatible donors by swapping their own willing but incompatible donors. With almost 70,000 patients already waiting for a cadaver kidney in the US, this market is seen as the only ethical way to significantly reduce the 4,000 deaths per year attributed to kidney disease. The clearing problem involves finding a social welfare maximizing exchange when the maximum length of a cycle is fixed. Long cycles are forbidden, since, for incentive reasons, all transplants in a cycle must be performed simultaneously. Also, in barterexchanges generally, more agents are affected if one drops out of a longer cycle. We prove that the clearing problem is NPhard. Solving it exactly is one of the main challenges in establishing a national kidney exchange. We present the first algorithm capable of clearing these markets on a nationwide scale. The key is incremental problem formulation. We adapt two paradigms for the task: constraint generation and column generation. For each, we develop techniques that dramatically improve both runtime and memory usage. We conclude that column generation scales drastically better than constraint generation.
Automatic Data Layout Using 01 Integer Programming
 In Proceedings of the International Conference on Parallel Architectures and Compilation Techniques (PACT94
, 1994
"... : The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet efficient machineindependent parallel programming model. By shifting much of the burden of machinedependent optimization to the compiler, the programmer is able to write dataparallel programs that ..."
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Cited by 64 (5 self)
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: The goal of languages like Fortran D or High Performance Fortran (HPF) is to provide a simple yet efficient machineindependent parallel programming model. By shifting much of the burden of machinedependent optimization to the compiler, the programmer is able to write dataparallel programs that can be compiled and executed with good performance on many different architectures. However, the choice of a good data layout is still left to the programmer. Even the most sophisticated compiler may not be able to compensate for a poorly chosen data layout since many compiler decisions are driven by the data layout specified in the program. The choice of a good data layout depends on many factors, including the target machine architecture, the compilation system, the problem size, and the number of processors available. The option of remapping arrays at specific points in the program makes the choice even harder. Current programming tools provide little or no support for this difficult sele...
Minimum cost capacity installation for multicommodity network flows
 MATHEMATICAL PROGRAMMING
, 1998
"... Consider a directed graph G = (V; A), and a set of traffic demands to be shipped between pairs of nodes in V. Capacity has to be installed on the edges of this graph (in integer multiples of a base unit) so that traffic can be routed. In this paper we consider the problem of minimum cost installatio ..."
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Cited by 63 (12 self)
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Consider a directed graph G = (V; A), and a set of traffic demands to be shipped between pairs of nodes in V. Capacity has to be installed on the edges of this graph (in integer multiples of a base unit) so that traffic can be routed. In this paper we consider the problem of minimum cost installation of capacity on the arcs to ensure that the required demands can be shipped simultaneously between node pairs. We study two different approaches for solving problems of this type. The first one is based on the idea of metric inequalities (see Onaga and Kakusho[1971]), and uses a formulation with only jAj variables. The second uses an aggregated multicommodity flow formulation and has jV j \Delta jAj variables. We first describe two classes of strong valid inequalities and use them to obtain a complete polyhedral description of the associated polyhedron for the complete graph on 3 nodes. Next we explain our solution methods for both of the approaches in detail and present computational results. Our computational experience shows that the two formulations are comparable and yield effective algorithms for solving reallife problems.
Issues in multirobot coalition formation
 IN PROC. MULTIROBOT SYST. FROM SWARMS TO INTELL. AUTOMATA
, 2006
"... As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in ..."
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Cited by 62 (4 self)
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As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in both super additive and nonsuper additive environments. The algorithmic techniques vary from negotiationbased protocols in multiagent system (MAS) environments to those based on computation in distributed problem solving (DPS) environments. Coalition formation behaviors have also been discussed in relation to game theory. Despite the plethora of MAS coalition formation literature, to the best of our knowledge none of the proposed algorithms have been demonstrated with an actual multirobot system. There exists a discrepancy between the multiagent algorithms and their applicability to the multirobot domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multirobot domain. A wellknown multiagent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its application to the multirobot domain. This paper reports multirobot coalition formation results based upon simulation and actual robot experiments. A multiagent coalition formation algorithm has been demonstrated on an actual robot system.
CABOB: A Fast Optimal Algorithm for Winner Determination in Combinatorial Auctions
, 2005
"... Combinatorial auctions where bidders can bid on bundles of items can lead to more economically efficient allocations, but determining the winners is NPcomplete and inapproximable. We present CABOB, a sophisticated optimal search algorithm for the problem. It uses decomposition techniques, upper and ..."
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Cited by 58 (9 self)
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Combinatorial auctions where bidders can bid on bundles of items can lead to more economically efficient allocations, but determining the winners is NPcomplete and inapproximable. We present CABOB, a sophisticated optimal search algorithm for the problem. It uses decomposition techniques, upper and lower bounding (also across components), elaborate and dynamically chosen bidordering heuristics, and a host of structural observations. CABOB attempts to capture structure in any instance without making assumptions about the instance distribution. Experiments against the fastest prior algorithm, CPLEX 8.0, show that CABOB is often faster, seldom drastically slower, and in many cases drastically faster—especially in cases with structure. CABOB’s search runs in linear space and has significantly better anytime performance than CPLEX. We also uncover interesting aspects of the problem itself. First, problems with short bids, which were hard for the first generation of specialized algorithms, are easy. Second, almost all of the CATS distributions are easy, and the run time is virtually unaffected by the number of goods. Third, we test several random restart strategies, showing that they do not help on this problem—the runtime distribution does not have a heavy tail.
Gomory Cuts Revisited
, 1996
"... In this paper, we investigate the use of Gomory's mixed integer cuts within a branchandcut framework. It has been argued in the literature that "a marriage of classical cutting planes and tree search is out of the question as far as the solution of largescale combinatorial optimization ..."
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Cited by 53 (5 self)
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In this paper, we investigate the use of Gomory's mixed integer cuts within a branchandcut framework. It has been argued in the literature that "a marriage of classical cutting planes and tree search is out of the question as far as the solution of largescale combinatorial optimization problems is concerned" [16] because the cuts generated at one node of the search tree need not be valid at other nodes. We show in this paper that it is possible, using a simple lifting procedure, to make Gomory cuts generated in a node of the enumeration tree globally valid in the case of mixed 01 programs. Other issues addressed in this paper are of computational nature, such as strategies for generating the cutting planes, deciding between branching and cutting, etc. The result is a robust mixed integer program solver. 1 Introduction In the late fifties and early sixties, Gomory [6], [7], [8] proposed to solve integer programs by using cutting planes, thus reducing integer programming to the solu...
An anytime algorithm for optimal coalition structure generation
 Journal of Artificial Intelligence Research (JAIR
"... Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multiagent syste ..."
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Cited by 50 (23 self)
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Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multiagent systems. Central to this endeavour is the problem of determining which of the many possible coalitions to form in order to achieve some goal. This usually requires calculating a value for every possible coalition, known as the coalition value, which indicates how beneficial that coalition would be if it was formed. Once these values are calculated, the agents usually need to find a combination of coalitions, in which every agent belongs to exactly one coalition, and by which the overall outcome of the system is maximized. However, this coalition structure generation problem is extremely challenging due to the number of possible solutions that need to be examined, which grows exponentially with the number of agents involved. To date, therefore, many algorithms have been proposed to solve this problem using different techniques — ranging from dynamic programming, to integer programming, to stochastic search — all of which suffer from major limitations relating to execution time, solution quality, and memory requirements.
Airline Crew Scheduling: A New Formulation and Decomposition Algorithm
 Operations Research
, 1995
"... Airline crew scheduling is concerned with finding a minimum cost assignment of flight crews to a given flight schedule while satisfying restrictions dictated by collective bargaining agreements and the Federal Aviation Administration. Traditionally, the problem has been modeled as a set partitioning ..."
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Cited by 47 (6 self)
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Airline crew scheduling is concerned with finding a minimum cost assignment of flight crews to a given flight schedule while satisfying restrictions dictated by collective bargaining agreements and the Federal Aviation Administration. Traditionally, the problem has been modeled as a set partitioning problem. In this paper, we present a new model based on breaking the decision process into two stages. In the first stage we select a set of duty periods that cover the flights in the schedule. Then, in the second stage, we attempt to build pairings using those duty periods. We suggest a decomposition approach for solving the model and present computational results for test problems provided by a major carrier. Our formulation provides a tighter linear programming bound than that of the conventional set partitioning formulation but is more difficult to solve. 1 Introduction In this paper we present a new formulation and decomposition approach for the airline crew scheduling problem. The ...