Function manual_weighted

examples/multi_objective.py:89–97

(h, X)

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# manual implementation of weighted multi-objective optimization
def manual_weighted(h, X):
    print('## Manual Weighted:\n')
    weights = np.asarray([1.0/(k+1) for k in range(OBJECTIVES)], dtype=np.float64)
    h.maximize(np.dot(weights[:,None] * profit, X).sum())

    print(f'  SOL: [{"".join(map(lambda x: "{:1.0f}".format(x), abs(h.vals(X))))}]')
    print(f'  OBJ: {pretty_print(np.dot(profit, h.vals(X)))}\n')

    print(f'  Obj: {h.getObjective()[0]}\n\n')


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