Search results for "Optimization problem"
showing 10 items of 281 documents
Decision Making on Pareto Front Approximations with Inherent Nondominance
2011
t Approximating the Pareto fronts of nonlinear multiobjective optimization problems is considered and a property called inherent nondominance is proposed for such approximations. It is shown that an approximation having the above property can be explored by interactively solving a multiobjective optimization problem related to it. This exploration can be performed with available interactive multiobjective optimization methods. The ideas presented are especially useful in solving computationally expensive multiobjective optimization problems with costly function value evaluations. peerReviewed
Scatter Search and Path Relinking
2011
Scatter search (SS) and path relinking (PR) are evolutionary methods that have been successfully applied to a wide range of hard optimization problems. The fundamental concepts and principles of the methods were first proposed in the 1970s and 1980s, and were based on formulations, dating back to the 1960s, for combining decision rules and problem constraints. The methods use strategies for search diversification and intensification that have proved effective in a variety of optimization problems and that have sometimes been embedded in other evolutionary methods to yield improved performance. This paper examines the scatter search and path relinking methodologies from both conceptual and p…
Linear Programming Based Methods for Solving Arc Routing Problems
2000
From the pioneering works of Dantzig, Edmonds and others, polyhedral (i.e. linear programming based) methods have been successfully applied to the resolution of many combinatorial optimization problems. See Junger, Reinelt & Rinaldi (1995) for an excellent survey on this topic. Roughly speaking, the method consists of trying to formulate the problem as a Linear Program and using the existing powerful methods of Linear Programming to solve it.
A Compact Representation of Preferences in Multiple Criteria Optimization Problems
2019
A critical step in multiple criteria optimization is setting the preferences for all the criteria under consideration. Several methodologies have been proposed to compute the relative priority of criteria when preference relations can be expressed either by ordinal or by cardinal information. The analytic hierarchy process introduces relative priority levels and cardinal preferences. Lexicographical orders combine both ordinal and cardinal preferences and present the additional difficulty of establishing strict priority levels. To enhance the process of setting preferences, we propose a compact representation that subsumes the most common preference schemes in a single algebraic object. We …
ε-Regularized two-level optimization problems: Approximation and existence results
2006
The purpose of this work is to improve some results given in [12], relating to approximate solutions for two-level optimization problems. By considering an e-regularized problem, we get new properties, under convexity assumptions in the lower level problems. In particular, we prove existence results for the solutions to the e-regularized problem, whereas the initial two-level optimization problem may fail to have a solution. Finally, as an example, we consider an approximation method with interior penalty functions.
Designing Paper Machine Headbox Using GA
2003
Abstract A non-smooth biobjective optimization problem for designing the shape of a slice channel in a paper machine headbox is described. The conflicting goals defining the optimization problem are the ones determining important quality properties of produced paper: 1) basis weight should be even and 2) the wood fibers of paper should mainly be oriented to the machine direction across the width of the whole paper machine. The novelty of the considered approach is that maximum deviations are used instead of least squares when objective functions are formed. For the solution of this problem, a multiobjective genetic algorithm based on nondominated sorting is considered. The numerical results…
Decision making in multiobjective optimization problems under uncertainty: balancing between robustness and quality
2018
As an emerging research field, multiobjective robust optimization employs minmax robustness as the most commonly used concept. Light robustness is a concept in which a parameter, tolerable degradations, can be used to control the loss in the objective function values in the most typical scenario for gaining in robustness. In this paper, we develop a lightly robust interactive multiobjective optimization method, LiRoMo, to support a decision maker to find a most preferred lightly robust efficient solution with a good balance between robustness and the objective function values in the most typical scenario. In LiRoMo, we formulate a lightly robust subproblem utilizing an achievement scalarizi…
Driven Primary Regulation for Minimum Power Losses Operation in Islanded Microgrids
2018
The paper proposes an improved primary regulation method for inverter-interfaced generating units in islanded microgrids. The considered approach employs an off-line minimum losses optimal power flow (OPF) to devise the primary frequency regulation curve’s set-points while satisfying the power balance, frequency and current constraints. In this way, generators will reach an optimized operating point corresponding to a given and unique power flow distribution presenting the minimum power losses. The proposed approach can be particularly interesting for diesel-based islanded microgrids that face, constantly, the issue of reducing their dependency from fossil fuels and of enhancing their gener…
Branch-and-Bound
2010
We now turn to the discussion of how to solve the linear ordering problem to (proven) optimality. In this chapter we start with the branch-and-bound method which is a general procedure for solving combinatorial optimization problems. In the subsequent chapters this approach will be realized in a special way leading to the so-called branch-and-cut method. There are further possibilities for solving the LOP exactly, e.g. by formulating it as dynamic program or as quadratic assignment problem, but these approaches did not lead to the implementation of practical algorithms and we will not elaborate on them here.
Drivetrain design optimization for electrically actuated systems via mixed integer programing
2015
The proposed paper presents a method to optimally select components of a drivetrain for an electrically actuated machine. A simple mathematical model of the machine is established and inequality constraints which determine the choice of drivetrain components are formulated. Elements to be picked (namely, a motor, a gearbox, and a drive) are taken from a discrete set of data provided in the catalogs of industrial motors and drives manufacturers. By solving an optimization problem, a combination of components which both satisfy design requirements and minimize the total drivetrain cost is selected. The operation of the selected drivetrain is verified against the motor loadability curves. In a…