Nonlinear Programming Codes: Information, Tests, Performance

ISBN-13: 9783540102472 / Angielski / Miękka / 1980 / 248 str.

Klaus Schittkowski

Opis

...The increasing importance of mathematical programming for the solution of complex nonlinear systems arising in practical situations requires the development of qualified optimization software. In recent years, a lot of effort has been made to implement efficient and reliable optimization programs and we can observe a wide distribution of these programs both for research and industrial applications. In spite of their practical importance only a few attempts have been made in the past to come to comparative conclusions and to give a designer the possibility to decide which optimization program could solve his individual problems in the most desirable way. Box [BO 1966J, Huang, Levy [HL 1970J, Himmelblau [HI 1971J, Dumi- tru [DU 1974], and More, Garbow, Hillstrom [MG 1978] for example compared algorithms for unres~ricied u~~illii~Gtiv~ y~~~le~~, B~~n [BD 1970], McKeown [MK 1975], and Ramsin, Wedin [RW 1977l studied codes for nonlinear least squares problems. Codes for the linear case are compared by Bartels [BA 1975.J and Schittkowski, Stoer [SS 1979J. Extensive tests for geometric programming algorithms are found in Dembo [DE 1976bJ, Rijckaert [RI 1977], and Rijckaert, Martens [RM 1978J.

Spis treści

I: Introduction.- II: Optimization methods.- 1. Line-search algorithms.- 2. Quadratic programming.- 3. Unconstrained optimization.- 4. Penalty methods.- 5. Multiplier methods.- 6. Quadratic approximation methods.- 7. Generalized reduced gradient methods.- 8. The method of Robinson.- III: Optimization programs.- 1. Program organization.- 2. Description of the programs.- IV: The construction of test problems.- 1. Fundamentals of the test problem generator.- 2. General test problems.- 3. Linearly constrained test problems.- 4. Degenerate test problems.- 5. Ill-conditioned test problems.- 6. Indefinite test problems.- 7. Convex test problems.- V: Performance evaluation.- 1. Notations.- 2. Efficiency, reliability, and global convergence.- 3. Performance for solving degenerate, ill-conditioned, and indefinite problems.- 4. Sensitivity to slight variations of the problem.- 5. Sensitivity to the position of the starting point.- 6. Ease of use.- 7. How to get a final score.- VI: Conclusions, recommendations, remarks.- 1. Pinal conclusions.- 2. Recommendations for the design of optimization programs.- 3. Some technical details.- Appendix A : Numerical data for constructing test problems.- Appendix B : Sensitivity analysis for the test problems.- Appendix C : Further results.- Appendix D : Evaluation of significance factors.- References.