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The smoothed number of Pareto optimal solutions in bicriteria integer optimization
 In Proc. of the 12th Int. Conf. on Integer Programming and Combinatorial Optimization (IPCO
, 2007
"... 1 Introduction We study integer optimization problems having two criteria, say profit andweight, which are to be optimized simultaneously. A common approach for solving such problems is generating the set of Pareto optimal solutions, also knownas the Pareto set. Pareto optimal solutions are optimal ..."
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Cited by 7 (4 self)
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1 Introduction We study integer optimization problems having two criteria, say profit andweight, which are to be optimized simultaneously. A common approach for solving such problems is generating the set of Pareto optimal solutions, also knownas the Pareto set. Pareto optimal solutions are optimal
Lower Bounds for the Smoothed Number of Pareto optimal Solutions
, 2011
"... In 2009, Röglin and Teng showed that the smoothed number of Pareto optimal solutions of linear multicriteria optimization problems is polynomially bounded in the number n of variables and the maximum density φ of the semirandom input model for any fixed number of objective functions. Their bound ..."
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Cited by 2 (1 self)
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In 2009, Röglin and Teng showed that the smoothed number of Pareto optimal solutions of linear multicriteria optimization problems is polynomially bounded in the number n of variables and the maximum density φ of the semirandom input model for any fixed number of objective functions. Their bound
A Provably Convergent Heuristic for Bicriteria Stochastic Integer Programming
"... The area of combinatorial optimization has been enlarged in the recent years into two directions: First, a huge number of articles deals with multiobjective combinatorial optimization (MOCO) problems, for which techniques to determine the set of Paretooptimal solutions have been developed (cf., e.g ..."
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The area of combinatorial optimization has been enlarged in the recent years into two directions: First, a huge number of articles deals with multiobjective combinatorial optimization (MOCO) problems, for which techniques to determine the set of Paretooptimal solutions have been developed (cf., e
Lower Bounds for the Average and Smoothed Number of Pareto Optima
"... Smoothed analysis of multiobjective 0–1 linear optimization has drawn considerable attention recently. In this literature, the number of Paretooptimal solutions (i.e., solutions with the property that no other solution is at least as good in all the coordinates and better in at least one) for multi ..."
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Cited by 3 (1 self)
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Smoothed analysis of multiobjective 0–1 linear optimization has drawn considerable attention recently. In this literature, the number of Paretooptimal solutions (i.e., solutions with the property that no other solution is at least as good in all the coordinates and better in at least one
Smoothed analysis of multiobjective optimization
 in FOCS, 2009
"... Abstract — We prove that the number of Paretooptimal solutions in any multiobjective binary optimization problem with a finite number of linear objective functions is polynomial in the model of smoothed analysis. This resolves a conjecture of René Beier [5]. Moreover, we give polynomial bounds on a ..."
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Cited by 12 (3 self)
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Abstract — We prove that the number of Paretooptimal solutions in any multiobjective binary optimization problem with a finite number of linear objective functions is polynomial in the model of smoothed analysis. This resolves a conjecture of René Beier [5]. Moreover, we give polynomial bounds
A genetic algorithm for a bicriteria supplier selection problem
"... Abstract In this paper, we discuss the problem of selecting suppliers for an organisation, where a number of suppliers have made price offers for supply of items, but have limited capacity. Selecting the cheapest combination of suppliers is a straightforward matter, but purchasers often have a dual ..."
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dual goal of lowering the number of suppliers they deal with. This second goal makes this issue a bicriteria problem minimisation of cost and minimisation of the number of suppliers. We present a mixed integer programming (MIP) model for this scenario. Quality and delivery performance are modelled
Smoothed analysis of integer programming
 IN PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON INTEGER PROGRAMMING AND COMBINATORIAL OPTIMIZATION (IPCO
, 2005
"... We present a probabilistic analysis of integer linear programs (ILPs). More specifically, we study ILPs in a socalled smoothed analysis in which it is assumed that first an adversary specifies the coefficients of an integer program and then (some of) these coefficients are randomly perturbed, e.g ..."
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Cited by 8 (1 self)
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We present a probabilistic analysis of integer linear programs (ILPs). More specifically, we study ILPs in a socalled smoothed analysis in which it is assumed that first an adversary specifies the coefficients of an integer program and then (some of) these coefficients are randomly perturbed, e
Decision making based on approximate and smoothed pareto curves
 In Proc. of 16th ISAAC
, 2005
"... We consider bicriteria optimization problems and investigate the relationship between two standard approaches to solving them: (i) computing the Pareto curve and (ii) the socalled decision maker’s approach in which both criteria are combined into a single (usually nonlinear) objective function. Pr ..."
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Cited by 11 (2 self)
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We consider bicriteria optimization problems and investigate the relationship between two standard approaches to solving them: (i) computing the Pareto curve and (ii) the socalled decision maker’s approach in which both criteria are combined into a single (usually nonlinear) objective function
An Efficient Method for Solving Bicriteria Solid Transportation Problem
"... Abstract: The solid transportation problem (STP) is known as one extension of the classical transportation problem and often arises in public distribution systems. In realworld situation, due to the complexity of the social and economic environments, it can also have with more then one objective fu ..."
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the transformation model of STP into twostage transportation problem. Double Prufer numbers are used to represent the candidate solution of the problem. The proposed algorithm is incorporated with problemspecific knowledge and conductive to find out a set of Pareto optimal solutions. Finally, we did a numerical
Twomachine flowshop scheduling with bicriteria problem
"... This paper attempts to solve a twomachine flowshop bicriteria scheduling problem with release dates for the jobs, in which the objective function is to minimize a weighed sum of total flow time and makespan. To tackle this scheduling problem, an integer programming model with N 2+3N variables and 5 ..."
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This paper attempts to solve a twomachine flowshop bicriteria scheduling problem with release dates for the jobs, in which the objective function is to minimize a weighed sum of total flow time and makespan. To tackle this scheduling problem, an integer programming model with N 2+3N variables
Results 1  10
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90