-->
^ F 5_
V ^h
" % ? 5_
V ^h N 5_ 5 5 8 v 8 ^i+
3 Z 5_ V
_o" 3 3 5_ " " ; v ; _o' E A Algorithm Selection and Configuration
5_ & v & _oP E ,
5_
: < v < _or E \ title="ParadisEO can be interfaced with other − Johann Dréo − CC-BY-SA" />5_
! v ! _o E m It is, for instance, easy to start with a simple local search, then add multi-objective capabilities, then shared-memory parallelization, then hybridization with an evolutionary algorithm and finally plug everything in an objective function so as to optimize the parameters with a particle swarm optimizer.
5_ v _o DAlgorithm Selection and Configuration
eParadiseo is organized in several modules, either providing different "grammars" for different algorithms, either providing high-level features. All modules follows the same architecture design and are interoperable with the others, so that you can easily choose the subset of features you need.
Paradiseo is organized in several modules, either providing different "grammars" for different algorithms, either providing high-level features. All modules follows the same architecture design and are interoperable with the others, so that you can easily choose the subset of features you need.
5_ $ v $ _p D b title="ParadisEO can be interfaced with other tools − Johann Dréo − CC-BY-SA" />5_ . . 8 v 8 _p D [ title="ParadisEO interfaced with other tools − Johann Dréo − CC-BY-SA" />5_ . 8 v 8 _p DParadiseo .
5_ % ' & v _r} DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation.
5_ & ( ' v _r DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically instanciate
5_ ' ) ( v _r DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" plugs in operators
5_ ( * ) v _r D +Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" plugs handle a set of operators
5_ ) + * % v _r D )Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators
5_ * , + R v _s D lParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled to form an algorithm.
5_ + - , } v _s" DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm.
5_ , . - } v _s, DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm, making the search space
5_ - / . ~ v _s/ DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. making the search space
5_ . 0 / C v C _s8 DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the making the search space
D 5_ / 1 0 C v C _s: DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo making the search space
5_ 0 2 1 C v C _s> DParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides making the search space
5_ 1 3 2 C v C _sQ D 'Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this is making the search space
5_ 2 4 3 C v C _sS D $Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this making the search space
5_ 3 5 4 C v C _sV D #Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this makes the search space
5_ 4 6 5 C v C _sc D /Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this makes the combination of different
5_ 5 7 6 C v C _se D 3Paradiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this can makes the combination of different
5_ 6 8 7 # C v C _sn D CParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of the combination of different
5_ 7 9 8 } C v C _s D YParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm. As the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them).
5_ 8 : 9 C v C _s FParadiseo provides meta-algorithmics features, like on-the-fly algorithm instanciation. This is useful to dynamically assemble and run an algorithm from a simple numerical encoding. This "algorithm forge" can handle a set of operators and parameter configurations, to be assembled in different "slots" to form an algorithm.
F 5_ 9 ; : C v C _s EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them).
5_ : < ; V _sAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them).
5_ ; = < V _s D D 5_ < > = V _s EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them).
5_ = ? > V _s EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). Given .
5_ > @ ? V _s EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). Given .
5_ ? A @ V _s E #As the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). If one plug this between an algorithm configurator (like irace).
5_ @ B A # v # _s E WAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). If one plug this between an algorithm configurator (like irace) and a fast benchmarking tool (like IOHexperimenter).
5_ A C B / # v # _t E KAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tool (like IOHexperimenter).
5_ B D C G # v # _t E LAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter).
5_ C E D l # v # _t' E pAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs.
5_ D F E # v # _tz EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (ParadisEO provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour.
5_ E G F # v # _t EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (ParadisEO provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour.
5_ F H G J v J _t EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (ParadisEO provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
E 5_ G I H J v J _t E OAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo ParadisEO provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ H J I J v J _t E NAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (ParadiseoParadisEO provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ I K J J v J _t E DAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseoprovides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ J L K 7 J v J _uF E EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ K M L : J v J _uL E QAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like <à href="">IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ L N M ? J v J _uP E PAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
E 5_ M O N J v J _uS E ~As the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ N P O J v J _u] EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ O Q P J v J _ub EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ P R Q J v J _un EAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
E 5_ Q S R ? 0 v _u ? A E ? @ E 5_ R T S @ & @ & @ 0 v 0 _u ? A F MAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ U W V _ FAs the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them!). To evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ V X W , _ GTo evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ W Y X _ GTo evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ X Z Y l _ H tYou can then wrap this evaluation within an optimizer, to automatically search for the best algorithm. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ Y [ Z w _ H }You can then wrap this evaluation within an optimizer, to automatically search for the best algorithm instance. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ Z \ [ _' H }You can then wrap this evaluation within an optimizer, to automatically search for the best algorithm instance. For instance, you can plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ [ ] \ v _9 HYou can then wrap this evaluation within an optimizer, to automatically search for the best algorithm instance. For instance, you can either use an optimizer made with , either plug this binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
5_ \ ^ ] I v I _D HYou can then wrap this evaluation within an optimizer, to automatically search for the best algorithm instance. For instance, you can either use an optimizer made with , either plug the binary with irace (Paradiseo provides an automatic interface generation) and reach budgets of 10 000 runs in just one hour (!).
H 5_ ] _ ^ v _U HTo evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for insanely fast runs.
5_ ^ ` _ v _W HTo evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for the fast runs.
5_ _ a ` v _[ HTo evaluate those algorithms, you can use bindings toward fast benchmarking tools (like IOHexperimenter), which allow for the fastests runs.
5_ ` b a v _t I H 5_ a c b v _v I <>5_ b d c v _w I5_ c e d v _z I
5_ d f e v _ IAnd voilà,
5_ e g f 0 v _ I QAnd voilà! You started by just listing interesting operators
5_ f h g X v _ I rAnd voilà! You started by just adding your idea to the existing listing interesting operators
5_ g i h G v _ I rAnd voilà! You started by just adding your idea to the existing list of interesting operators
5_ h j i m v _ I qAnd voilà! You started by just adding your idea to an existing list of interesting operators
5_ i k j v _ IAnd voilà! You started by just adding your idea to an existing list of interesting operators, and you can check.
5_ j l k { v _ IAnd voilà! You started by just adding your idea to an existing list of interesting operators, and you can check if it's worth .
5_ k m l v _ IAnd voilà! You started by just adding your idea to an existing list of interesting operators, and you can now just check if it's worth .
5_ l n m v _ IAnd voilà! You started by just adding your idea to an existing list of interesting operators, and you can now just check if it allows for better algorithms.
5_ m o n 0 0 N v M _ IAnd voilà! You started by just adding your idea to an existing list of interesting operators, and you can now check if it allows for better algorithms.
5_ n p o a 0 N v M _ IAnd voilà! You started by just making a high-level list of interesting operators, and you can now check if it allows for better algorithms.
5_ o q p [ 0 N v M _ IAnd voilà! You started by just designing a high-level view of your solver, and you can now check if it allows for better algorithms.
5_ p r q ^ 0 N v M _ IAnd voilà! You started by just designing a high-level view of your solver and you can now check if it allows for better algorithms.
5_ q s r Z 0 N v M _ IAnd voilà! You started by just designing a high-level view of your solver and you can now check if it allows for better algorithms.
5_ r t s l 0 N v M _ IAnd voilà! You started by just designing a high-level view of your solver, and you can now check if it allows for better algorithms.
5_ s u t 0 N v M _ IAnd voilà! You started by just designing a high-level view of your solver, and you can now easily check if it allows for better algorithms.
5_ t v u 0 N v M _X IAnd voilà! You started by just designing a high-level view of your solver, and you can now easily check if it allows for better performance.
5_ u w v 0 N v M _\ IAnd voilà! You started by just designing a high-level view of your solver, and you can now easily check if it allows for better performance. Ohlala.
5_ v x w 0 N v M _` IAnd voilà! You started by just designing a high-level view of your solver, and you can now easily check if it allows for better performance. Ohlala.
5_ w y x v _ I xAnd voilà! You started by just designing a high-level view of your solver, and you can now easily check if it allows for better performance. Ohlala.
5_ z | { a a z v y _ IAnd voilà! You started by just designing a high-level view of a solver, and you can now easily check if it allows for better performance. Ohlala.
5_ { } | j j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now have allows for better performance. Ohlala.
5_ | ~ } m j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now have the solver which have better performance. Ohlala.
5_ } ~ s j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now have th solver which have better performance. Ohlala.
5_ ~ p j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now know which have better performance. Ohlala.
5_ v j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now know which solver have better performance. Ohlala.
5_ j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now know which algorithm instance allow for have better performance. Ohlala.
5_ j t v s _ IAnd voilà! You started by just designing a high-level view of a solver, and you now know which algorithm instance allow for the better performance. Ohlala.
5_ j t v s _2 J I 5_ j t v s _7 J 5_ @ @ L v L _o J Note that the binding with IOHexperimenter also allow to automatically explore some run data in the IOHanalyzer GUI.
5_ O O V v V _x J xNote that the binding with IOHexperimenter also allow to easily explore some run data in the IOHanalyzer GUI.
5_ t t v v v _ J |Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer GUI.
5_ h t v v v _ J |Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer HMI.
5_ s t v v v _ JNote that the binding with IOHexperimenter also allow to easily explore experimental data in the 5_ m t v v v _ J Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer HMI. Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer HMI. Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer HMI. Note that the binding with IOHexperimenter also allow to easily explore experimental data in the IOHanalyzer HMI. Note that the binding with IOHexperimenter also allow to easily explore experimental results in the IOHanalyzer HMI. And voilà! You started by just designing a high-level view of a solver, and you now know which algorithm instance allow for the best performance. Ohlala. Note that the binding with IOHexperimenter also allow to easily import and explore experimental results in the IOHanalyzer HMI. As the Paradiseo codebase provides generic algorithm and a large set of operators, this can make a huge number of algorithms alternatives (easily millions of them!). As the Paradiseo codebase provides generic algorithm and a large set of operators, it's easy to have access to a huge number of algorithms alternatives (easily millions of them!). As the Paradiseo codebase provides generic algorithm and a large set of operators, it's easy to have access to a huge number of algorithms alternatives. (easily millions of them!). As the Paradiseo codebase provides generic algorithm and a large set of operators, it's easy to have access to a huge number of algorithms alternatives: there's easily millions of them!).