Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce an Embarrassingly Parallel Search (EPS) method for solving constraint problems in parallel, and  show that this method matches or even outperforms state-of-the-art algorithms on a number of problems using various computing infrastructures. EPS is a simple method in which a master decomposes the problem into many disjoint subprob-lems which are then solved independently by workers. Our approach has three advantages: it is an efficient method; it involves almost no communication or synchronization beten workers; and its implementation is made easy because the master and the workers rely on an underlying constraint solver, but does not require to modify it.  describes the method, and its applications to various constraint problems (satisfaction, enumeration, optimization).  show that our method can be adapted to different underlying solvers (Gecode, Choco2, OR-tools) on different computing infrastructures (multi-core, data centers , cloud computing). The experiments cover unsatisfiable, enumeration and optimization problems, but do not cover first solution search because it makes the results hard to analyze. The same variability can be observed for optimization problems, but at a lesser extent because the optimality proof is required. EPS offers good average performance, and matches or outperforms other available parallel implementations of Gecode as ll as some solvers portfolios. Moreover,  perform an in-depth analysis of the various factors that make this approach efficient as ll as the anomalies that can occur. Last,  show that the decomposition is a key component for efficiency and load balancing.
['Arnaud Malapert', 'Jean-Charles Régin', 'Mohamed Ali Rezgui']
I am writing a research paper on a idea Embarrassingly Parallel Search in Constraint Programming
[{"from": "human", "value": "I am writing a research paper on a idea Embarrassingly Parallel Search in Constraint Programming"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce an Embarrassingly Parallel Search (EPS) method for solving constraint problems in parallel, and  show that this method matches or even outperforms state-of-the-art algorithms on a number of problems using various computing infrastructures. EPS is a simple method in which a master decomposes the problem into many disjoint subprob-lems which are then solved independently by workers. Our approach has three advantages: it is an efficient method; it involves almost no communication or synchronization beten workers; and its implementation is made easy because the master and the workers rely on an underlying constraint solver, but does not require to modify it.  describes the method, and its applications to various constraint problems (satisfaction, enumeration, optimization).  show that our method can be adapted to different underlying solvers (Gecode, Choco2, OR-tools) on different computing infrastructures (multi-core, data centers , cloud computing). The experiments cover unsatisfiable, enumeration and optimization problems, but do not cover first solution search because it makes the results hard to analyze. The same variability can be observed for optimization problems, but at a lesser extent because the optimality proof is required. EPS offers good average performance, and matches or outperforms other available parallel implementations of Gecode as ll as some solvers portfolios. Moreover,  perform an in-depth analysis of the various factors that make this approach efficient as ll as the anomalies that can occur. Last,  show that the decomposition is a key component for efficiency and load balancing."}]