Solving Graph Optimization Problems in a Framework for Monte-Carlo Search
نویسندگان
چکیده
In this paper we solve fundamental graph optimization problems like Maximum Clique and Minimum Coloring with recent advances of Monte-Carlo Search. The optimization problems are implemented as single-agent games in a generic state-space search framework, roughly comparable to what is encoded in PDDL for an action planner.
منابع مشابه
INTRODUCTION AND DEVELOPMENT OF SURROGATE MANAGEMENT FRAMEWORK FOR SOLVING OPTIMIZATION PROBLEMS
In this paper, we have outlined the surrogate management framework for optimization of expensive functions. An initial simple iterative method which we call the “Strawman” method illustrates how surrogates can be incorporated into optimization to stand in for the most expensive function. These ideas are made rigorous by incorporating them into the framework of pattern search methods. The SMF al...
متن کاملSolving the Fixed Channel Assignment Problem in Cellular Communications Using An Adaptive Local Search
The Channel Assignment Problem can be defined as assigning a minimum number of radio frequencies to a set of transceiver/receiver units without violating given constraints, in particular the frequency separation that must exist between two given channels to avoid interference. Being an NPcomplete problem, finding good quality solutions increases in difficulty as the number of transceiver/receiv...
متن کاملRELIABILITY-BASED DESIGN OPTIMIZATION OF COMPLEX FUNCTIONS USING SELF-ADAPTIVE PARTICLE SWARM OPTIMIZATION METHOD
A Reliability-Based Design Optimization (RBDO) framework is presented that accounts for stochastic variations in structural parameters and operating conditions. The reliability index calculation is itself an iterative process, potentially employing an optimization technique to find the shortest distance from the origin to the limit-state boundary in a standard normal space. Monte Carlo simulati...
متن کاملEFFICIENCY OF IMPROVED HARMONY SEARCH ALGORITHM FOR SOLVING ENGINEERING OPTIMIZATION PROBLEMS
Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In order to overcome the various difficultie...
متن کاملA Comparison of Monte Carlo Tree Search and Mathematical Optimization for Large Scale Dynamic Resource Allocation
Dynamic resource allocation (DRA) problems are an important class of dynamic stochastic optimization problems that arise in a variety of important real-world applications. DRA problems are notoriously difficult to solve to optimality since they frequently combine stochastic elements with intractably large state and action spaces. Although the artificial intelligence and operations research comm...
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:
دوره شماره
صفحات -
تاریخ انتشار 2017