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A snapshot of the summary - Operation Research Techniques 1
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1 Mathematically modelling
This is a preview. There are 8 more flashcards available for chapter 1
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Give the definition of solution of an optimization problemA solution to an optimization problem is a collection of values of the decision variables.
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Give the definition of feasible region of an optimization problemThe feasible region of an optimization problem is the set of feasible solutions to the problem.
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Give the definition of unbounded problem of an
optimization problemAnoptimization problem isunbouded if for any feasible solution x, there exists another feasible solution y whose value is better than the value of x. It has nofinite optimal solution. -
Give the definition of infeasible problem of an optimization problemA mathematical program is infeasible if there are no feasible solutions. No solution that satisfies all constraints and bounds.
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What is the proportionality assumption of linear programming?The
assumption that when it takes 3 eggs to make 1 chocolate cake. It takes 9 eggs to make 3 chocolate cakes.
Thisassumption has to hold to be able to applylinear programming . -
What is meant with the divisibility assumption?A variable can be infinitely divisible and still have meaning.
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When are problems called discrete or combinatorial optimization problems?When all the variables are binary.
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What is meant with a static and a dynamic model?In a static model the decision variables do not involve a sequence of decisions over multiple periods. In a dynamic model the decision variables do involve sequences of decisions over multiple periods.
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What is meant with deterministic and stochastic models?In a deterministic problem the value of the objective function and whether or not the constraints are satisfied is known with certainty. Otherwise stochastic.
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What is the isocost line?The line on which you can find an optimal solution considering a minimization problem.
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The following topics are covered in this summary
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constraint, myf, fo
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graph, tree, lines
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phase, artificial, variable
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dual, primal, problem
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solution, heuristic, problem
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running, algorithm, time
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problems, np, concise
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problem, polynomially, np-complete
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solution, approximate, approximation
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problem, dispatching, approach
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factor, priority, regret
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solution, local, tabu
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chain, markov, sa
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degree, destroy, solution