Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A Constraint Satisfaction Problem is defined by a set of variables and a set of constraints, each variable has a nonempty domain of possible values. Each constraint involves some subset of the variables and specifies the allowable combinations of values for that subset. A solution of the problem is defined by an assignment of values to some or all of the variables that does not violate any constraints. To solve an instance, a search tree is created and each node in the tree represents a variable of the instance. The order in which the variables are selected for instantiation changes the form of the search tree and affects the cost of finding a solution.   explore the use of a Choice Function to dynamically select from a set of variable ordering heuristics the one that best matches the current problem state in order to show an acceptable performance over a wide range of instances. The Choice Function is defined as a ighted sum of process indicators expressing the recent improvement produced by the heuristic recently used. The ights are determined by a Particle Swarm Optimization algorithm in a multilevel approach.  report results where our combination of strategies outperforms the use of individual strategies.
['Broderick Crawford', 'Ricardo Soto', 'Eric Monfroy', 'Wenceslao Palma', 'Carlos Castro', 'Fernando Paredes']
I am writing a research paper on a idea Parameter tuning of a choice-function based hyperheuristic using Particle Swarm Optimization
[{"from": "human", "value": "I am writing a research paper on a idea Parameter tuning of a choice-function based hyperheuristic using Particle Swarm Optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A Constraint Satisfaction Problem is defined by a set of variables and a set of constraints, each variable has a nonempty domain of possible values. Each constraint involves some subset of the variables and specifies the allowable combinations of values for that subset. A solution of the problem is defined by an assignment of values to some or all of the variables that does not violate any constraints. To solve an instance, a search tree is created and each node in the tree represents a variable of the instance. The order in which the variables are selected for instantiation changes the form of the search tree and affects the cost of finding a solution.   explore the use of a Choice Function to dynamically select from a set of variable ordering heuristics the one that best matches the current problem state in order to show an acceptable performance over a wide range of instances. The Choice Function is defined as a ighted sum of process indicators expressing the recent improvement produced by the heuristic recently used. The ights are determined by a Particle Swarm Optimization algorithm in a multilevel approach.  report results where our combination of strategies outperforms the use of individual strategies."}]