Minor fixes and refactoring on local search and genetic algorithms #141
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…t.__init__() Indeed: - the objective is systematically overwritten before first iteration in local search algorithms (only places used: SimulatedAnnealing, HillClimber, and HillClimberPareto), and the corresponding solution is available at that point, so we can fill it then - the objective was generally bad initialized using model.evaluate (which gives a dictionary) instead of aggreg_from_dict_values(model.evaluate()) at is correctly done inside local search algos.
nhuet
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nb_solutionsattribute from local search solverscurrent_solutionandcurrent_objectivefromRestartHandlerLimit.__init__():objective was already overwritten during local search algo's
solve()and generally badly initialized in examples (usingmodel.evaluate()which gives a dictionary instead of a fitness value).