Buscar
Estás en modo de exploración. debe iniciar sesión para usar MEMORY

   Inicia sesión para empezar

level: Level 1 of Lecture 4 - Knowledge Engineering - MiniZinc

Questions and Answers List

level questions: Level 1 of Lecture 4 - Knowledge Engineering - MiniZinc

QuestionAnswer
Constraints programming is usually done in two steps:1) Creation of an conceptual model, an abstraction of some real-world problem. 2) Design of a program that solves the problem
MiniZincMiniZinc is a modeling language being developed mostly by NICTA (Australia) MiniZinc ⊂ Zinc – a more powerful modeling language
Running MiniZincMiniZinc models must have mzn extension and data dzn
A MiniZinc model consists of a sequence of itemsAn inclusion item include <filename (string)>; An output item output <list of string expressions>; Declaration of a variable A constraint constraint <Boolean expression>; A solve item (only one of the following is allowed) - solve satisfy; - solve maximize <arith. expression>; - solve minimize <arith. expression>; predicates and asserts (for checking parameter values) Search annotation items ann
Writing Efficient Models IAdd search annotations to the solve item to control exploration of the search space first_fail (MRV): choose the variable with the smallest domain size indomain_min: assign the variable its smallest domain value See reference manual for a complete list of heuristics
Writing Efficient Models IIUse global constraints such as alldifferent since they have better propagation behavior Try different models for the problem Add redundant constraints Bound variables as tightly as possible (avoid var int) Avoid introducing unnecessary variables
SummaryMiniZinc is a language designed for specification of decision and optimisation problems The model is declarative, although it can contain annotations The language provides large number of operators and built-in functions to simplify modelling Advanced models in MiniZinc use predicates to define complex subproblem constraints Global constraints (better solving) User defined constraints (better readability) Efficiency depends on the model formulation Developing an efficient decision model requires sometimes considerable experimentation (NP-hard problems are hard problems)