检索结果-内蒙古大学图书馆

IEEE International Conference on Service Operations and Logistics and Informatics

作者： Zhou, Qiang Cui, Xunxue Chuzhou Univ Dept Comp Sci & Technol Chuzhou Peoples R China New Star Res Inst Appl Technol Hefei Peoples R China

ISBN: (纸本)9781424420124

Flow-shop scheduling problems are generally studied in a single-objective deterministic way whereas they are multiobjective and are subjected to a wide range of uncertainties. Although evolutionary algorithms are commonly used to solve multiobjective and stochastic problems, very few approaches combine simultaneously these two aspects. In the paper the multiobjective flow shop scheduling problem is modeled with the stochastic processing time and the machine breakdown. A mathematical scheme is designed for the largest flow of time and the largest delay time. A hybrid multiobjective genetic algorithm is proposed to solve the optimization problems iteratively on uncertain condition. The results of simulation experiments arc shown that the algorithm can provide a good performance for the flow shop scheduling problems on the uncertain condition.

关键词： flow shop scheduling uncertainty multiobjective combinatorial optimization genetic algorithm stochastic processing times

来源：评论

学校读者我要写书评

暂无评论

An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization 05

An empirical study on the handling of overlapping solutions ...

引用

Genetic and Evolutionary Computation Conference

作者： Ishibuchi, Hisao Narukawa, Kaname Nojima, Yusuke Osaka Prefecture Univ Grad Sch Engn Sakai Osaka 5998531 Japan

ISBN: (纸本)1595930108

We focus on the handling of overlapping solutions in evolutionary multiobjective optimization (EMO) algorithms. First we show that there exist a large number of overlapping solutions in each population when EMO algorithms are applied to multiobjective combinatorial optimization problems with only a few objectives. Next we implement three strategies to handle overlapping solutions. One strategy is the removal of overlapping solutions in the objective space. In this strategy, overlapping solutions in the objective space are removed during the generation update phase except for only a single solution among them. As a result, each solution in the current population has a different location in the objective space. Another strategy is to remove overlapping solutions so that each solution in the current population has a different location in the decision space. The other strategy is the modification of Pareto ranking where overlapping solutions in the objective space are allocated to different fronts. As a result, each solution in each front has a different location in the objective space. Effects of each strategy on the performance of the NSGA-II algorithm are examined through computational experiments on multiobjective 0/1 knapsack problems, multiobjective flowshop scheduling problems, and multiobjective fuzzy rule selection problems.

关键词： algorithms evolutionary multiobjective optimization (EMO) multiobjective combinatorial optimization diversity of non-dominated solutions diversity-preserving strategies NSGA-II

来源：评论

学校读者我要写书评

暂无评论

Choquet optimization Using GAI Networks for Multiagent/Multicriteria Decision-Making

Choquet Optimization Using GAI Networks for Multiagent/Multi...

引用

1st International Conference Algorithmic Decision Theory

作者： Dubus, Jean-Philippe Gonzales, Christophe Perny, Patrice LIP6 UPMC F-75016 Paris France

ISBN: (纸本)9783642044274

This paper is devoted to preference-based recommendation or configuration in the context of multiagent (or multicriteria) decision making. More precisely, we study the use of decomposable utility functions in the search for Choquet-optimal solutions on combinatorial domains. We consider problems where the alternatives (feasible solutions) are represented as elements of a product set of finite domains and evaluated according to different points of view (agents or criteria) leading to different objectives. Assuming that objectives take the form of GAI-utility functions over attributes, we investigate the use of GAI networks to determine efficiently an element maximizing an overall utility function defined by a Choquet integral.

关键词： GAI-nets Choquet Integral multiobjective combinatorial optimization Multiagent Decision-Making Preference-based Configuration

来源：评论

学校读者我要写书评

暂无评论

How to Choose Solutions for Local Search in multiobjective combinatorial Memetic Algorithms

How to Choose Solutions for Local Search in Multiobjective C...

引用

11th International Conference on Parallel Problem Solving from Nature

作者： Ishibuchi, Hisao Hitotsuyanagi, Yasuhiro Wakamatsu, Yoshihiko Nojima, Yusuke Osaka Prefecture Univ Dept Comp Sci & Intelligent Syst Grad Sch Engn Naka Ku Sakai Osaka 5998531 Japan

ISBN: (纸本)9783642158438

This paper demonstrates that the performance of multiobjective memetic algorithms (MOMAs) for combinatorial optimization strongly depends on the choice of solutions to which local search is applied. We first examine the effect of the tournament size to choose good solutions for local search on the performance of MOMAs. Next we examine the effectiveness of an idea of applying local search only to non-dominated solutions in the offspring population. We show that this idea has almost the same effect as the use of a large tournament size because both of them lead to high selection pressures. Then we examine different configurations of genetic operators and local search in MOMAs. For example, we examine the use of genetic operators after local search. In this case, improved solutions by local search are used as parents for recombination while local search is applied to the current population after generation update.

关键词： multiobjective genetic local search (MOGLS) evolutionary multiobjective optimization (EMO) hybrid algorithms memetic algorithms multiobjective combinatorial optimization

来源：评论

学校读者我要写书评

暂无评论

2-additive Choquet Optimal Solutions in multiobjective optimization Problems

2-additive Choquet Optimal Solutions in Multiobjective Optim...

引用

15th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU)

作者： Lust, Thibaut Rolland, Antoine Univ Paris 06 CNRS LIP6 Sorbonne Univ Paris France Univ Lyon 1 ERIC Villeurbanne France

ISBN: (纸本)9783319087955;9783319087948

In this paper, we propose a suffcient condition for a solution to be optimal for a 2-additive Choquet integral in the context of multiobjective combinatorial optimization problems. A 2-additive Choquet optimal solution is a solution that optimizes at least one set of parameters of the 2-additive Choquet integral. We also present a method to generate 2-additive Choquet optimal solutions of multiobjective combinatorial optimization problems. The method is experimented on some Pareto fronts and the results are analyzed.

关键词： Choquet integral Multicriteria decision making Fuzzy measure multiobjective combinatorial optimization k-additivity

来源：评论

学校读者我要写书评

暂无评论

Committee Selection with a Weight Constraint Based on a Pairwise Dominance Relation

Committee Selection with a Weight Constraint Based on a Pair...

引用

2nd International Conference on Algorithmic Decision Theory, ADT 2011

作者： Delort, Charles Spanjaard, Olivier Weng, Paul UPMC CNRS LIP6 UMR 7606 F-75005 Paris France

ISBN: (纸本)9783642248726

This paper is devoted to a knapsack problem with a cardinality constraint when dropping the assumption of additive representability [10]. More precisely, we assume that we only have a classification of the items into ordered classes. We aim at generating the set of preferred subsets of items, according to a pairwise dominance relation between subsets that naturally extends the ordering relation over classes [4,16]. We first show that the problem reduces to a multiobjective knapsack problem with cardinality constraint. We then propose two polynomial algorithms to solve it, one based on a multiobjective dynamic programming scheme and the other on a multiobjective branch and bound procedure. We conclude by providing numerical tests to compare both approaches.

关键词： Committee selection Ordinal combinatorial optimization multiobjective combinatorial optimization Knapsack with cardinality constraint Polynomial algorithms

来源：评论

学校读者我要写书评

暂无评论

Incorporation of decision maker's preference into evolutionary multiobjective optimization algorithms 06

Incorporation of decision maker's preference into evolutiona...

引用

8th Annual Genetic and Evolutionary Computation Conference

作者： Ishibuchi, Hisao Nojima, Yusuke Narukawa, Kaname Doi, Tsutomu Osaka Prefecture Univ Grad Sch Engn Dept Comp Sci & Intelligent Syst Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

ISBN: (纸本)9781595931863

The main characteristic feature of evolutionary multiobjective optimization (EMO) is that no a priori information about the decision maker's preference is utilized in the search phase. EMO algorithms try to find a set of well-distributed Pareto-optimal solutions with a wide range of objective values. It is, however, very difficult for EMO algorithms to find a good solution set of a multiobjective combinatorial optimization problem with many decision variables and/or many objectives. In this paper, we propose an idea of incorporating the decision maker's preference into EMO algorithms to efficiently search for Pareto-optimal solutions of such a hard multiobjective optimization problem.

关键词： evolutionary multiobjective optimization (EMO) many-objective optimization multiobjective combinatorial optimization decision maker's preference balance between convergence and diversity

来源：评论

学校读者我要写书评

暂无评论

Determining location and size of medical departments in a hospital network: A multiobjective decision support approach

引用

Health Care Management Science 2004年第1期7卷 63-71页

作者： Stummer, Christian Doerner, Karl Focke, Axel Heidenberger, Kurt Sch. of Bus. Econ. and Comp. Sci. University of Vienna A-1210 Vienna Bruenner Str. 72 Austria

Decisions on the location and size of medical departments in a given hospital network are prime examples of priority setting in health care, which is an issue of growing political importance. As such decisions are regularly characterized by multiple and often conflicting objectives in real-life, this paper integrates the fields of hospital planning and multiobjective decision support. The proposed two-phase solution procedure for our corresponding mathematical programming model does not require a priori preference information. Instead, it seeks efficient solutions by means of multiobjective tabu search in the first phase, while applying clustering in the second phase to allow the decision makers to interactively explore the solution space until the "best" configuration is determined. The real-world applicability of our approach is illustrated through a numerical example based on hospital data from Germany.

关键词： Clustering Hospital planning Interactive decision support multiobjective combinatorial optimization Tabu search

来源：评论

学校读者我要写书评

暂无评论

Learning to Balance Exploration and Exploitation in Pareto Local Search for Multi-objective combinatorial optimization 22

Learning to Balance Exploration and Exploitation in Pareto L...

引用

Genetic and Evolutionary Computation Conference (GECCO)

作者： Zhang, Haotian Shi, Jialong Sun, Jianyong Xu, Zongben Xi An Jiao Tong Univ Xian Shaanxi Peoples R China

ISBN: (纸本)9781450392686

As a natural extension of local search, Pareto local search (PLS) is a basic building block in many state-of-the-art metaheuristics for multi-objective combinatorial optimization problems (MCOPs). However, the basic PLS suffers from a low convergence rate, since it always fully explores the neighborhood of each unexplored solution, which is unnecessary. Some studies tried to introduce heuristic design in PLS to balance exploration and exploitation. In this paper, we handle this issue by a learning based framework. In the framework, PLS applies the firstK strategy, namely it stops exploring a solution's neighborhood when it obtains K non-dominated solutions, where K is adaptively controlled by a neural network based on observations collected during the search. Training the neural network is modeled as a reinforcement learning problem. Thus the proposed PLS variant is called PLSNN. In the experiments, we compared the performance of PLSNN and several PLS variants with heuristic design on the multi-objective unconstrained binary quadratic programming problem (mUBQP). The experimental results show that PLSNN performed significantly better than its counterparts on all test instances.

关键词： multiobjective combinatorial optimization Pareto local search reinforcement learning neural networks

来源：评论

学校读者我要写书评

暂无评论

Using Bound Sets in multiobjective optimization: Application to the Biobjective Binary Knapsack Problem

Using Bound Sets in Multiobjective Optimization: Application...

引用

9th International Symposium on Experimental Algorithms

作者： Delort, Charles Spanjaard, Olivier Univ Paris 06 CNRS LIP6 F-75005 Paris France

ISBN: (纸本)9783642131929

This paper is devoted to a study of the impact of using bound sets in biobjective optimization. This notion, introduced by Villareal and Karwan [19], has been independently revisited by Ehrgott and Candibleux [9], as well as by Sourd and Spanjaard [17]. The idea behind it is very general, and can therefore be adapted to a wide range of biobjective combinatorial problem. We focus here on the biobjective binary knapsack problem. We show that using bound sets in a two-phases approach [18] based on biobjective dynamic programming yields numerical results that outperform previous ones, both in execution times and memory requirements.

关键词： multiobjective combinatorial optimization bound sets biobjective binary knapsack problem

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：