Output-sensitive Complexity of Multiobjective Combinatorial Optimization
نویسندگان
چکیده
We study output-sensitive algorithms and complexity for multiobjective combinatorial optimization problems. In this computational complexity framework, an algorithm for a general enumeration problem is regarded efficient if it is output-sensitive, i.e., its running time is bounded by a polynomial in the input and the output size. We provide both practical examples of MOCO problems for which such an efficient algorithm exists as well as problems for which no efficient algorithm exists under mild complexity theoretic assumptions.
منابع مشابه
Recent Advances in Multiobjective Optimization
Multiobjective (or multicriteria) optimization is a research area with rich history and under heavy investigation within Operations Research and Economics in the last 60 years [1,2]. Its object of study is to investigate solutions to combinatorial optimization problems that are evaluated under several objective functions – typically defined on multidimensional attribute (cost) vectors. In multi...
متن کاملA novel elitist multiobjective optimization algorithm: Multiobjective extremal optimization
Recently, a general-purpose local-search heuristic method called Extremal Optimization (EO) has been successfully applied to some NP-hard combinatorial optimization problems. This paper presents an investigation on EO with its application in multiobjective optimization and proposes a new novel elitist (1+ λ ) multiobjective algorithm, called Multiobjective Extremal Optimization (MOEO). In order...
متن کاملA Simple yet Efficient Multiobjective Combinatorial Optimization Method Using Decomposition and Pareto Local Search
Combining ideas from evolutionary algorithms, decomposition approaches and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: MoMad. It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MoMad evolves three populations: popula...
متن کاملA Feature-Based Performance Analysis in Evolutionary Multiobjective Optimization
This paper fundamentally investigates the performance of evolutionary multiobjective optimization (EMO) algorithms for computationally hard 0–1 combinatorial optimization, where a strict theoretical analysis is generally out of reach due to the high complexity of the underlying problem. Based on the examination of problem features from a multiobjective perspective, we improve the understanding ...
متن کاملSatellite Conceptual Design Multi-Objective Optimization Using Co Framework
This paper focuses upon the development of an efficient method for conceptual design optimization of a satellite. There are many option for a satellite subsystems that could be choice, as acceptable solution to implement of a space system mission. Every option should be assessment based on the different criteria such as cost, mass, reliability and technology contraint (complexity). In this rese...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1610.07204 شماره
صفحات -
تاریخ انتشار 2016