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@@ -13,9 +13,9 @@ An invalid solution can be shown below where the sum of the object weights is gr
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:width: 800 px
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:align: center
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-Hence, ``[1, 0, 1, 0, 0]`` is an invalid solution.
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+In fact, **[1, 0, 1, 0, 0]** is an invalid solution as we have a weight of **16** which violates the knapsack capacity constraint.
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-To avoid taking into account invalid solutions, we can define our function which will validate or not a solution.
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+To avoid taking into account invalid solutions, we can define our function which will validate or not a solution based on our problem instance:
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.. code-block:: python
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@@ -27,17 +27,38 @@ To avoid taking into account invalid solutions, we can define our function which
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elements_weight = [ 12, 1, 4, 1, 2 ] # weight of each object
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"""
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- validator function definition
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+ Validator function definition
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"""
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def validator(solution):
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weight_sum = 0
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for i, w in enumerate(elements_weight):
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+ # add weight if current object is set to 1
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weight_sum += w * solution._data[i]
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+ # validation condition
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return weight_sum <= 15
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4.2. Use of validator
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-~~~~~~~~~~~~~~~~~~~~~
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+~~~~~~~~~~~~~~~~~~~~~
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+
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+We can now generate solutions randomly by passing our validation function as a parameter:
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+
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+.. code-block:: python
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+
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+ """
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+ Problem instance definition
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+ """
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+ ...
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+
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+ """
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+ Validator function definition
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+ """
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+ ...
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+
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+ # ensure valid solution
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+ solution = BinarySolution.random(5, validator)
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+
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+ The validation of a solution is therefore now possible. In the next part we will focus on the evaluation of a solution.
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