The MOSEK Python optimizer API manual Version 7.0 (Revision 141)
Optimizer API for Python - Documentation - Mosek Optimizer API for Python - Documentation - Mosek
184 CHAPTER 14. PRIMAL FEASIBILITY REPAIR 47 # call the main function 48 try: 49 main (sys.argv[1]) 50 except Exception as e: 51 print (e) 52 raise will produce the same output as the command line tool discussed in Section 14.3.1.
Chapter 15 Sensitivity analysis 15.1 Introduction Given an optimization problem it is often useful to obtain information about how the optimal objective value changes when the problem parameters are perturbed. E.g, assume that a bound represents a capacity of a machine. Now, it may be possible to expand the capacity for a certain cost and hence it is worthwhile knowing what the value of additional capacity is. This is precisely the type of questions the sensitivity analysis deals with. Analyzing how the optimal objective value changes when the problem data is changed is called sensitivity analysis. 15.2 Restrictions Currently, sensitivity analysis is only available for continuous linear optimization problems. Moreover, MOSEK can only deal with perturbations in bounds and objective coefficients. 15.3 References The book [1] discusses the classical sensitivity analysis in Chapter 10 whereas the book [17] presents a modern introduction to sensitivity analysis. Finally, it is recommended to read the short paper [18] to avoid some of the pitfalls associated with sensitivity analysis. 185
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Chapter 15<br />
Sensitivity analysis<br />
15.1 Introduction<br />
Given an optimization problem it is often useful to obtain information about how the optimal objective<br />
value changes when the problem parameters are perturbed. E.g, assume that a bound represents a<br />
capacity of a machine. Now, it may be possible to expand the capacity for a certain cost and hence it<br />
is worthwhile knowing what the value of additional capacity is. This is precisely the type of questions<br />
the sensitivity analysis deals with.<br />
Analyzing how the optimal objective value changes when the problem data is changed is called sensitivity<br />
analysis.<br />
15.2 Restrictions<br />
Currently, sensitivity analysis is only available for continuous linear optimization problems. Moreover,<br />
<strong>MOSEK</strong> can only deal with perturbations in bounds and objective coefficients.<br />
15.3 References<br />
<strong>The</strong> book [1] discusses the classical sensitivity analysis in Chapter 10 whereas the book [17] presents<br />
a modern introduction to sensitivity analysis. Finally, it is recommended to read the short paper [18]<br />
to avoid some of the pitfalls associated with sensitivity analysis.<br />
185
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