Combining cellular genetic algorithms and local search for solving satisfiability problems
نویسندگان
چکیده
A new parallel hybrid method for solving the satissa-bility problem that combines cellular genetic algorithms and the random walk (W SAT) strategy of GSAT is presented. The method, called CGWSAT, uses a cellular genetic algorithm to perform a global search on a random initial population of candidate solutions and a local selective generation of new strings. Global search is specialized in local search by adopting the WSAT strategy. CGWSAT has been implemented on a Meiko CS-2 parallel machine using a two-dimensional cellular automaton as parallel computation model. The algorithm has been tested on randomly generated problems and some classes of problems from the DIMACS test set.
منابع مشابه
Solving a Stochastic Cellular Manufacturing Model by Using Genetic Algorithms
This paper presents a mathematical model for designing cellular manufacturing systems (CMSs) solved by genetic algorithms. This model assumes a dynamic production, a stochastic demand, routing flexibility, and machine flexibility. CMS is an application of group technology (GT) for clustering parts and machines by means of their operational and / or apparent form similarity in different aspects ...
متن کاملSolving the Ride-Sharing Problem with Non-Homogeneous Vehicles by Using an Improved Genetic Algorithm with Innovative Mutation Operators and Local Search Methods
An increase in the number of vehicles in cities leads to several problems, including air pollution, noise pollution, and congestion. To overcome these problems, we need to use new urban management methods, such as using intelligent transportation systems like ride-sharing systems. The purpose of this study is to create and implement an improved genetic algorithms model for ride-sharing with non...
متن کاملMathematical Programming Models for Solving Unequal-Sized Facilities Layout Problems - a Generic Search Method
This paper present unequal-sized facilities layout solutions generated by a genetic search program named LADEGA (Layout Design using a Genetic Algorithm). The generalized quadratic assignment problem requiring pre-determined distance and material flow matrices as the input data and the continuous plane model employing a dynamic distance measure and a material flow matrix are discussed. Computa...
متن کاملParallel hybrid method for SAT that couples genetic algorithms and local search
A parallel hybrid method for solving the satisfiability (SAT) problem that combines cellular genetic algorithms (GAs) and the random walk SAT (WSAT) strategy of greedy SAT (GSAT) is presented. The method, called cellular genetic WSAT (CGWSAT), uses a cellular GA to perform a global search from a random initial population of candidate solutions and a local selective generation of new strings. Gl...
متن کاملImproved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having ‘g’ operations is performed on ‘g’ operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem...
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 1998