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Algorithmic Improvements on Dynamic Programming for the Biobjective {0,1} Knapsack Problem
"... This paper presents several methodological and algorithmic improvements over a stateoftheart dynamic programming algorithm for solving the biobjective {0, 1} knapsack problem. The variants proposed make use of new definitions of lower and upper bounds, which allow a large number of states to be ..."
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This paper presents several methodological and algorithmic improvements over a stateoftheart dynamic programming algorithm for solving the biobjective {0, 1} knapsack problem. The variants proposed make use of new definitions of lower and upper bounds, which allow a large number of states
Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach
 IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
, 1999
"... Evolutionary algorithms (EA’s) are often wellsuited for optimization problems involving several, often conflicting objectives. Since 1985, various evolutionary approaches to multiobjective optimization have been developed that are capable of searching for multiple solutions concurrently in a singl ..."
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Cited by 813 (22 self)
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single run. However, the few comparative studies of different methods presented up to now remain mostly qualitative and are often restricted to a few approaches. In this paper, four multiobjective EA’s are compared quantitatively where an extended 0/1 knapsack problem is taken as a basis. Furthermore, we
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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with loops (undirected cycles). The algorithm is an exact inference algorithm for singly connected networks the beliefs converge to the cor rect marginals in a number of iterations equal to the diameter of the graph.1 However, as Pearl noted, the same algorithm will not give the correct beliefs for mul
On local search for biobjective knapsack problems, in "Evolutionary Computation
 DOI : 10.1162/EVCO_A_00074], http:// hal.inria.fr/hal00676625
"... In this article, a local search approach is proposed for three variants of the biobjective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set is cond ..."
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Cited by 2 (0 self)
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In this article, a local search approach is proposed for three variants of the biobjective binary knapsack problem, with the aim of maximizing the total profit and minimizing the total weight. First, an experimental study on a given structural property of connectedness of the efficient set
A minimal algorithm for the 01 Knapsack Problem.
 Operations Research
, 1994
"... Although several large sized 01 Knapsack Problems (KP) may be easily solved, it is often the case that most of the computational eort is used for preprocessing, i.e. sorting and reduction. In order to avoid this problem it has been proposed to solve the socalled core of the problem: A Knapsack ..."
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Cited by 49 (10 self)
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Although several large sized 01 Knapsack Problems (KP) may be easily solved, it is often the case that most of the computational eort is used for preprocessing, i.e. sorting and reduction. In order to avoid this problem it has been proposed to solve the socalled core of the problem: A Knapsack
New Trends in Exact Algorithms for the 01 Knapsack Problem
, 1997
"... While the 1980s were focused on the solution of large sized "easy" knapsack problems, this decade has brought several new algorithms, which are able to solve "hard" large sized instances. We will give an overview of the recent techniques for solving hard knapsack problems, with s ..."
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Cited by 42 (0 self)
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, with special emphasis on the addition of cardinality constraints, dynamic programming, and rudimentary divisibility. Computational results, comparing all recent algorithms, are presented. 1 Introduction We consider the classical 01 Knapsack Problem (KP) where a subset of n given items has to be packed in a
An expandingcore algorithm for the exact 01 Knapsack Problem.
 European Journal of Operational Research
, 1993
"... A new branchandbound algorithm for the exact solution of the 01 Knapsack Problem is presented. The algorithm is based on solving an "expanding core", which initially only contains the break item, but which is expanded each time the branchandbound algorithm reaches the border of the co ..."
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Cited by 31 (7 self)
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A new branchandbound algorithm for the exact solution of the 01 Knapsack Problem is presented. The algorithm is based on solving an "expanding core", which initially only contains the break item, but which is expanded each time the branchandbound algorithm reaches the border
Surrogate upper bound sets for biobjective bidimensional binary knapsack problems
"... Abstract The paper deals with the definition and the computation of surrogate upper bound sets for the biobjective bidimensional binary knapsack problem. It introduces the Optimal Convex Surrogate Upper Bound set, which is the tightest possible definition based on the convex relaxation of the sur ..."
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Abstract The paper deals with the definition and the computation of surrogate upper bound sets for the biobjective bidimensional binary knapsack problem. It introduces the Optimal Convex Surrogate Upper Bound set, which is the tightest possible definition based on the convex relaxation
Genetic Algorithms for 0/1 Multidimensional Knapsack Problems
 Proceedings Norsk Informatikk Konferanse, NIK '96
, 1996
"... An important class of combinatorial optimization problems are the Multidimensional 0/1 Knapsacks, and various heuristic and exact methods have been devised to solve them. Among these, Genetic Algorithms have emerged as a powerful new search paradigms. We show how a proper selection of parameters and ..."
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Cited by 5 (1 self)
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An important class of combinatorial optimization problems are the Multidimensional 0/1 Knapsacks, and various heuristic and exact methods have been devised to solve them. Among these, Genetic Algorithms have emerged as a powerful new search paradigms. We show how a proper selection of parameters
Implementing an efficient fptas for the 0–1 multiobjective knapsack problem
"... In the present work we are interested in the practical behavior of a new fptas to solve the approximation version of the 01 multiobjective knapsack problem. The proposed methodology makes use of very general techniques (such as dominance relations in dynamic programming) and thus may be applicable ..."
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Cited by 4 (1 self)
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In the present work we are interested in the practical behavior of a new fptas to solve the approximation version of the 01 multiobjective knapsack problem. The proposed methodology makes use of very general techniques (such as dominance relations in dynamic programming) and thus may
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