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On the performance of multiple-objective genetic local search on the 0/1 knapsack problem - A comparative experiment

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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION 2002年第4期6卷 402-412页

作者： Jaszkiewicz, A Poznan Univ Tech Inst Comp Sci PL-60965 Poznan Poland

multiple-objective metaheuristics, e.g., jective evolutionary algorithms, constitute one of the most fields of multiple-objective optimization. Since 1985, a number of different methods have been proposed. However, few comparative studies of the methods were performed on scale problems. In this paper, we continue two comparative iments on the multiple-objective 0/1 knapsack problem in the literature. We compare the performance of two jective genetic local search (MOGLS) algorithms to the best formers in the previous experiments using the same test The results of our experiment indicate that our MOGLS generates better approximations to the nondominated set in same number of functions evaluations than the other algorithms.

关键词： evolutionary algorithms hybrid algorithms knapsack problem metaheuristics multiple-objective optimization

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multiple-objective based model predictive control of pulse jet fabric filters

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CHEMICAL ENGINEERING RESEARCH & DESIGN 2000年第A4期78卷 581-589页

作者： Ju, J Chiu, MS Tien, C Natl Univ Singapore Dept Chem & Environm Engn Singapore 119260 Singapore

With the increasingly stringent emissions regulations of fine particulates and air toxics, pulse jet fabric filters have become an attractive particulate collection option for utilities. Despite their wide application, the present control algorithm used in fabric filtration systems can best be described as rudimentary. In this paper, a model predictive control (MPC) technique is employed owing to its distinct advantages. Unlike its conventional counterpart, the proposed MPC algorithm takes the economic factor into consideration, which is formulated in a multiple-objective optimization framework. To avoid the local optimum, a global optimization technique is incorporated into the proposed MPC design. Simulation results show that the proposed multiple-objective optimization based MPC design method is especially suitable to the pulse jet fabric filtration process, where the set point change and process disturbance occur frequently.

关键词： model predictive control pulse jet fabric filter multiple-objective optimization

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Utility function programs and optimization over the efficient set in multiple-objective decision making

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JOURNAL OF optimization THEORY AND APPLICATIONS 1997年第3期92卷 605-631页

作者： Horst, R Thoai, NV INST MATH HANOI 10000VIETNAM

Natural basic concepts in multiple-objective optimization lead to difficult multiextremal global optimization problems. Examples include detection of efficient points when nonconvexities occur, and optimization of a linear function over the efficient set in the convex (even linear) case. Assuming that a utility function exists allows one to replace in general the multiple-objective program by a single, nonconvex optimization problem, which amounts to a minimization over the efficient set when the utility function is increasing. A new algorithm is discussed for this utility function program which, under natural mild conditions, converges to an E-approximate global solution in a finite number of iterations. Applications include linear, convex, indefinite quadratic, Lipschitz, and d.c. objectives and constraints.

关键词： multiple-objective optimization utility function programs global optimization branch-and-bound algorithms

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Using multicriterion optimization to classify ecosystems from multitemporal imagery

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PHYSICAL GEOGRAPHY 1996年第3期17卷 282-293页

作者： Ridgley, MA Aerts, JCJH RESOURCE ANAL BV NL-2611 SJ DELFT NETHERLANDS

One element of research on climate change is modeling of the non-fossil carbon cycle. Non-fossil carbon models such as IMAGE-2 use ecosystem maps as inputs for calculating the production of carbon and the levels of carbon in the atmosphere. The NFOSEUR project aims to classify European ecosystems from remote sensing (RS) data. The data consist of monthly NDVI values for each year, where NDVI is a measure of the photosynthetic activity of the ecosystems. Each ecosystem has a characteristic NDVI curve throughout the year, yielding a characteristic ''fingerprint'' far each ecosystem. Until now classification of RS data has been based on various statistical procedures. This paper discusses the use of multicriterion optimization to determine the ''best'' classification. Coal programming and compromise goal programming models yield classifications that compare closely with those produced by conventional statistical approaches. Case studies include a classification of ecosystems far Germany and southern France. Various potential improvements to our models are discussed, including new formulations and the prospects for fuzzy linear and goal programming models.

关键词： multiple-objective optimization remote sensing classification ecosystems

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Computation of Nash equilibria: Admissibility of parallel gradient descent

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JOURNAL OF optimization THEORY AND APPLICATIONS 1996年第1期90卷 45-61页

作者： Bozma, HI Associate Professor Department of Electrical and Electronic Engineering Boğazici University Bebek Istanbul Turkey

This paper offers some analytical results on the practical computation of Nash equilibria, which has been demonstrated to be relevant in real-world applications. In particular, the parallel gradient descent is analyzed from this perspective, and admissibility conditions are presented. First, the parallel gradient descent is defined in terms of update strategies and iteration times. It is shown that convergence is related to the contraction property. The analysis then derives sufficient conditions for the update strategies and the iteration times that ensure convergence. An illustrative example is presented in order to demonstrate practical implementation aspects and motivate the practical use of game theory in a wide spectrum of applications varying from economics to intelligent sensor systems.

关键词： multiple-objective optimization Nash games practical algorithms parallel decision making

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ON THE UTOPIAN APPROACH TO THE MULTIobjective LQ PROBLEM

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OPTIMAL CONTROL APPLICATIONS & METHODS 1993年第2期14卷 111-124页

作者： DENICOLAO, G LOCATELLI, A POLITECN MILAN DIPARTIMENTO ELETTRONVIA PONZIO 34-5I-20133 MILANITALY POLITECN MILAN DIPARTIMENTO ELETTRONCNRCTR TEORIA SISTEMII-20133 MILANITALY

The infinite horizon, multiobjective linear quadratic control problem for continuous time systems is considered. Following a utopian approach, the optimal solution is defined as the solution that minimizes the distance from the utopian point in the cost space. It is shown that under standard stabilizability and detectability assumptions the optimal solution always exists. The solution coincides with the solution of a scalar LQ problem in which the cost matrices are given by a suitably weighted sum of their counterparts in the individual criteria. By exploiting the characterization and properties of the optimal solution, it is shown that the problem can be efficiently solved by means of a Newton-type algorithm.

关键词： multiple-objective optimization LINEAR QUADRATIC CONTROL PARETO OPTIMALITY UTOPIAN POINT METHOD

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AN INTERACTIVE METHOD FOR multiple-objective MATHEMATICAL-PROGRAMMING PROBLEMS

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JOURNAL OF optimization THEORY AND APPLICATIONS 1991年第3期68卷 539-561页

作者： SHIN, WS RAVINDRAN, A UNIV OKLAHOMA IND ENGNNORMANOK 73019

An interactive method is developed for solving the general nonlinear multiple objective mathematical programming problems. The method asks the decision maker to provide partial information (local tradeoff ratios) about his utility (preference) function at each iteration. Using the information, the method generates an efficient solution and presents it to the decision maker. In so doing, the best compromise solution is sought in a finite number of iterations. This method differs from the existing feasible direction methods in that (i) it allows the decision maker to consider only efficient solutions throughout, (ii) the requirement of line search is optional, and (iii) it solves the problems with linear objective functions and linear utility function in one iteration. Using various problems selected from the literature, five line search variations of the method are tested and compared to one another. The nonexisting decision maker is simulated using three different recognition levels, and their impact on the method is also investigated.

关键词： multiple-objective optimization MATHEMATICAL PROGRAMMING INTERACTIVE METHODS TRADEOFF CUTTING PLANE

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OPTIMAL DYNAMIC SCHEDULING OF A POWER-GENERATION SYSTEM TO SATISFY multiple CRITERIA

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SIMULATION 1991年第4期56卷 241-249页

作者： FOROUZBAKHSH, F DEITERS, RM KERMANSHAHI, BS TOKYO METROPOLITAN UNIV FAC TECHNOLDEPT ELECT ENGN2-1-1 FUKAZAWASETAGAYA KUTOKYO 158JAPAN

A computer algorithm for the optimal scheduling of generators in a power system is presented and tested. The algorithm, based on goal programming, automatically and dynamically schedules the output of each generator in the system for optimal operation. The optimal operation can take into consideration multiple objectives such as economy, security, and reduction of pollution as well as practical constraints. To validate and test the algorithm, an example system of 5 generators, 10 busses, and 11 transmission lines is optimized for two objectives: minimal generation cost and minimal emission of nitrous oxides (NOx). Hourly changes in total power demand in the range of 90% to 110% are considered together with a constraint of maximum permissible total NOx emission. Other practical equality and inequality constraints are incorporated into the optimization algorithm. The simulation results demonstrate that the outputs of the generators can be changed smoothly and dynamically. Furthermore, using the algorithm, computer control is practicable either by direct on-line optimization or by using the feasible operation region generated as a small data-base by off-line computation.

关键词： ELECTRICAL POWER SYSTEM OPTIMAL SCHEDULING GOAL PROGRAMMING multiple-objective optimization DYNAMIC SCHEDULING

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WEIGHTING FACTOR RESULTS IN VECTOR optimization

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JOURNAL OF optimization THEORY AND APPLICATIONS 1988年第3期58卷 411-430页

作者： DURIER, R 1.Laboratoire d'Analyse Numérique Université de Dijon Dijon France

This paper deals with the study, in a convex vector optimization problem, of the set of efficient solutions and the set of properly efficient solutions, the latter being obtained by a weighting factor technique. Relationships between these two sets are discussed; they are shown to be nonempty when the objective functions have no common direction of recession and to be closed and equal when, moreover, the objective functions are locally polyhedral. An example is provided where the set of efficient solutions is not included in the closure of the nonempty set of properly efficient solutions.

关键词： multiple-objective optimization efficient points properly efficient points recession cones recession functions

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OPTIMALITY CONDITIONS IN NONCONICAL multiple-objective PROGRAMMING

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JOURNAL OF optimization THEORY AND APPLICATIONS 1983年第1期40卷 25-60页

作者： HAZEN, GB MORIN, TL PURDUE UNIV SCH IND ENGNW LAFAYETTEIN 47907

Previous theoretical work in multiple-objective optimization has focused entirely on vector orders representable by positive cones. Here, we treat multiple-objective problems in which solutions are sought which are maximal (efficient, nondominated) under an order which may be nonconical. Compactness conditions under which maximal solutions exist and bound the remaining alternatives are given. First-order necessary conditions and first-order sufficient conditions for maximality in general normed linear spaces are derived, and a scalarization result is given. A small computational example is also presented. Several previous results are special cases of those given here.

关键词： multiple-objective optimization vector optimization existence theorems first-order optimality conditions normed linear spaces

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