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scipy.optimize can only do single-criterion optimization (scalar-valued objective function instead of vector-valued objective functions).
by ogrisel 10y ago
scipy.optimize can only do single-criterion optimization (scalar-valued objective function instead of vector-valued objective functions).
- radarsat1 10y ago> The tradeoffs between these two criteria can either be managed by some supervisory decision maker (the driver of the car in this example) or by merging the multiple criteria into some single criteria and phrasing the problem as a standard optimization problem. You always have to reduce the problem to a scalar if you want a single answer.
- ogrisel 10y agoYou might want to discover the full Pareto frontier to gain some insights on the structure of the trade-off. I think the best methods to explore the Pareto frontier are based on the concepts of evolutionary computation like NSGA-II and SPEA-2: https://en.wikipedia.org/wiki/Multi-objective_optimization#A_posteriori_methods https://en.wikipedia.org/wiki/Multi-objective_optimization#A...
- oli5679 10y agoTrue, you need to assign weights to a vector of outputs as discussed in this article. After that, scipy.optimize is easy to use though.