# root/PythonPackages/OpenOpt/ChangeLog.txt

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1 | See |

2 | http://openopt.org/Changelog |

3 | for more convenient rendering |

4 | |

5 | |

6 | 0.25 (2009-September-15) |

7 | * Minor changes for NLP/NSP solver ralg |

8 | * Some bugfixes, lots of code clean up |

9 | * OpenOpt can optimize FuncDesigner models, for some non-linear classes it provides automatic differentiation |

10 | Backward incompatibilities: |

11 | * oovar-oofun have been moved to standalone package (FuncDesigner) |

12 | * For some problems with nonlinear funcs, where user-supplied derivatives are absent, you should have DerApproximator installed. |

13 | |

14 | |

15 | 0.24 (2009-June-15) |

16 | * New class: MINLP - mixed-integer nonlinear problems |

17 | * New class: Linear Uniform Norm Problems (LUNP) |

18 | * Now DFP can handle user-supplied derivatives |

19 | * Some changes for finite-difference derivatives approximation |

20 | * New handling of linear equality constraints by ralg and some other changes for the solver |

21 | * Some important bugfixes, code cleanup, minor doc improvements |

22 | Backward incompatibilities: |

23 | * Connection to PSwarm 1.4 instead of 1.3 (Python API is backward-incompatible for 1.4) |

24 | * Default p.storeIterPoints set to False (it affects r.iterValues.x - for large scale problems it eats quite lot of memory) |

25 | |

26 | |

27 | 0.23 (2009-March-15) |

28 | * New class SDP (solvers: CVXOPT and DSDP) |

29 | * New class SOCP (solvers: CVXOPT, in future CVXOPT authors intend to connect DSDP SOCP solver, then it will be connected to OO) |

30 | * New class DFP (Data Fit Problem, syntax similar to MATLAB lsqcurvefit) |

31 | * Some changes to NLP/NSP solver ralg |

32 | * Some more minor changes, code cleanup, bugfixes |

33 | Changes for named variables syntax: |

34 | * Check derivatives for oofun |

35 | * oolin constraints now are rendered into linear ones, provided all inputs of the oolin involved are oovar instances |

36 | Contributors: |

37 | * Thanks to Stepan Hlushak for writing GLP solver "de" (based on differential evolution) |

38 | Backward incompatibilities: |

39 | * if you provide derivatives for constraints, then for each constraint c_i or h_j: R^n -> R^s_k you should provide dc_i or dh_j with exactly same number of outputs, i.e. R^n -> R^(s_k, n), otherwise correct solution is not guaranteed (for named variables syntax you shouldn't care of the issue, each oofun has single function for obtaining output and no more than a single user-provided function for obtaining output derivatives). |

40 | |

41 | 0.21 (2008-December-15) : |

42 | * major changes for NLP / NSP solver ralg |

43 | * new converter: qp2nlp |

44 | * new converter: lp2nlp |

45 | * new converter: nllsp2nlp |

46 | * new converter: nlsp2nlp |

47 | * new converter: minimax to NLP |

48 | * Introducing OpenOpt GUI |

49 | * PSwarm 1.3 has been connected instead of v 1.1. It has much more parameters to modify and ability to use user-supplied callback function. |

50 | * Lots of changes related to oofun: add oovar and oolin, now fixed oovars can be correctly handled |

51 | * enhanced iterfcn connection for scipy fmin_cobyla |

52 | * some doc updates for result structure |

53 | * new openopt API func: oosolver |

54 | * some code cleanup and bugfixes |

55 | * some other minor changes |

56 | Backward incompatibilities: |

57 | * instead of "from scikits.openopt import ..." now you should use "from openopt import ..." |

58 | * LSP has been renamed to NLLSP (Non-Linear Least Squares Problem) |

59 | * for oofuns support of ordinary variables (x) had been ceased (it's hard to keep maintaining), use oovars instead. |

60 | |

61 | 0.19 (2008-September-15) : |

62 | * Some changes for NLP/NSP solver ralg (especially related to handling linear constraints Ax <= b, Aeq x = beq, lb <= x <= ub) |

63 | * Bugfix for ralg IPOPT linear constraints handling |

64 | * ALGENCAN v 2.0.x has been connected (v 1.0 is no longer supported, v 2.0.3 or later is required) |

65 | * bugfix for constrained NLSP graphic output (constrained nssolve isn't turned to latest ralg version yet) |

66 | * scale parameter for lpSolve (p.scale = {False} | True | 0 | 1) |

67 | * New OO class LLAVP (linear least absolute values aka linear least deviations) |

68 | * Improved handling of non-linear functions with restricted dom |

69 | * GLP (global) solver galileo now can handle integer problems (via p.useInteger = 1 or True) |

70 | * Another one GLP solver connected: pswarm |

71 | * Lots of work related to oofun concept (see OO Doc page for details) |

72 | * Add converters llsp2nlp, llavp2nsp |

73 | * Convenient handling of maximization problems (via p.goal = 'max' or 'maximum') |

74 | * Some code clean up and bugfixes |

75 | Backward incompatibility: |

76 | * Changed objective function in LLSP |

77 | * MATLAB-style gradtol renamed to gtol (for to provide same syntax to scipy.optimize fmin_bfgs, fmin_cg and less-to-type) |

78 | |

79 | 0.18 (2008-June-15) : |

80 | * connection to glpk MILP solver (requires cvxopt v >= 1.0) |

81 | * connection to NLP solver IPOPT (requires pyipopt installation, that is currently available for Linux only) |

82 | * major changes for ralg |

83 | * splitting non-linear constraints can benefit for some solvers |

84 | * unified text output for NLP solvers |

85 | * handling of maximization problems (via p.goal = 'max' or 'maximum') |

86 | * some bugfixes, lots of code cleanup |

87 | |

88 | 0.17 (2008-March-15) : |

89 | * new classes: GLP (global problem), MMP (mini-max problem) |

90 | * several new solvers written: goldenSection, nsmm |

91 | * some more solvers connected: scipy_slsqp, bvls, galileo |

92 | * possibility to change default solver parameters |

93 | * user-defined callback functions |

94 | * changes in auto derivatives check |

95 | * "noise" parameter for noisy functions |

96 | * some changes to NLP/NSP solver ralg |

97 | * some changes in graphical output: initial estimations xlim, ylim |

98 | * scaling |

99 | * some bugfixes |

100 | |

101 | 0.15 (2007-December-15): |

102 | * some new classes |

103 | * several new solvers written |

104 | * some more solvers connected |

105 | * NLP/NSP solver ralg can handle constrained problems |

106 | * some bugfixes |

107 | * some enhancements in graphical output (especially for constrained problems) |

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