def search(problem, heuristic, usegN, astar):
    """Multifunctional Algorithm"""
    fringe = util.PriorityQueue()
    generated = {}
    n = node.Node(problem.getStartState())
    fringe.push(n, 0)#el cost=0 ja que es el node inicial
    generated[n.state] = ['F', n]

    while True:
        #TEST OBJETIVO
        if fringe.isEmpty():
            print "No Solution"
            sys.exit(-1)
        n = fringe.pop()
        if problem.isGoalState(n.state):
            return n.path()
            print "Solution"
        if not generated[n.state][0] == 'E':
            generated[n.state] = ['E', n]
            #GENERAR SUCESORES
            for s, a, c in problem.getSuccessors(n.state):
                #FUNCION DE COSTE ADAPTABLE AL ALGORITMO
                fdeNsuc = max(n.fdeN * astar, heuristic(s, problem) + (n.gdeN + c) * usegN)
                ns = node.Node(s, n, a, fdeNsuc, n.gdeN + c)
                #CONTROLAR NODOS YA EXPANDIDOS O EN EL FRINGE
                if not generated.get(ns.state) == None:
                    if generated.get(ns.state)[0] == 'E':
                        continue
                    if generated.get(ns.state)[0] == 'F' and generated[ns.state][1].fdeN <= ns.fdeN:
                        continue
                fringe.push(ns, fdeNsuc)
                generated[ns.state] = ['F', ns]