batch Optimal Design of Multiproduct Batch Plant. Source: G.R. Kocis & I.E. Grossmann, "Global OPtimization of Nonconvex Mixed Integer Nonlinear Programmming (MINLP) problems in Process Synthesis", Indust. Engng. Chem. Res., No. 27, pp 1407--1421, 1988.

c-reload-14(a-f) Small core reload pattern optimization problem for 14 fuel positions. Source: A.J. Quist, R. van Geemert, J.E. Hoogenboom, T. Illes, E. de Klerk, T. Terlaki, "Optimization of a Nuclear Reactor Core Reload Pattern Using Nonlinear Optimization and Search Heuristics", Technical Report, Delft University, 1997.

c-reload-q-(24,25,49,104) Small core reload pattern optimization problem for 24, 25, 49 and 104 fuel positions respectively. Modelling a quadrant (rather than octant) of the core. Own problem generated from c-reload-14(a-f).

c-sched(1,2) Source: V. Jain & I.E. Grossmann, "Cyclic Scheduling of Continuous Parallel Units with Decaying Performance", AIChE Journal, 44, 1623-1636.

feedloc Feed tray location & determination of optimum number of trays in a distillation column.

geartrain Gear Train design problem. Source: E. Sangren, "Nonlinear Integer and Discrete Programming in Mechanical Design Optimization", Trans. ASME, J. Mech. Design 112, 223-229, 1990.

lbti-00-* Optimal design of a load-bearing thermal insulation system. This model is discontinuous (model (P-0)) in Abhishek, Leyffer, andf Linderoth, "Modeling without Categorical Variables: A Mixed-Integer Nonlinear Program for the Optimization of Thermal Insulation Systems", Argonne MCS Preprint, ANL/MCS-P1434-0607, 2007.

lbti-01-* Optimal design of a load-bearing thermal insulation system. This model is nonsmooth (model (P-1)) in Abhishek, Leyffer, andf Linderoth, "Modeling without Categorical Variables: A Mixed-Integer Nonlinear Program for the Optimization of Thermal Insulation Systems", Argonne MCS Preprint, ANL/MCS-P1434-0607, 2007.

lbti-02-* Optimal design of a load-bearing thermal insulation system. This model is smooth (model (P-2)) in Abhishek, Leyffer, andf Linderoth, "Modeling without Categorical Variables: A Mixed-Integer Nonlinear Program for the Optimization of Thermal Insulation Systems", Argonne MCS Preprint, ANL/MCS-P1434-0607, 2007.

mittelman Pure integer NLP due to Hans D. Mittelman, Arizona State University, [email protected].

optprloc Optimal positioning of a new product in a multiattribute space: market of M existing products, set of N consumers in a multiattribute space of dimension K. Source: M. Duran & I.E. Grossmann, "An outer approximation algorithm for a class of mixed integer nonlinear programs", Mathematical Programming 36, pp. 307-339, 1986.

space-(25,960) Model of 25 and 960 resp. bar space truss design.

1. Model discrete sizes as SOS-1 variables

2. Units kips, in; except for density in lbs/in^3

3. Optimum weight in lbs

Source: GAMS file by F. Tin-Loi, University of New South Wales, April 00.

space-(25,960)-r Reduced model of 25 and 960 resp. bar space truss design (making use of ampl's defined variable capability to remove some variables from space(25,960)-r

1. Model discrete sizes as SOS-1 variables

2. Units kips, in; except for density in lbs/in^3

3. Optimum weight in lbs

Source: GAMS file by F. Tin-Loi, University of New South Wales, April 00.

space-960-i Model of 960 bar space truss design from space-960-r with SOS 1 variables replaced by integer.

1. Units kips, in; except for density in lbs/in^3

2. Optimum weight in lbs

Source: GAMS file by F. Tin-Loi, University of New South Wales, April 00.

space-960-ir Model of 960 bar space truss design. Combines space-960-r and space-960-i (i.e. integers replacing SOS & ampl's defined variables).

1. Units kips, in; except for density in lbs/in^3

2. Optimum weight in lbs

Source: GAMS file by F. Tin-Loi, University of New South Wales, April 00.

space-(25,960)-r Reduced model of 25 and 960 resp. bar space truss design (making use of ampl's defined variable capability to remove some variables from space(25,960)-r

1. Model discrete sizes as SOS-1 variables

2. Units kips, in; except for density in lbs/in^3

3. Optimum weight in lbs

Source: GAMS file by F. Tin-Loi, University of New South Wales, April 00.

spring Coil compression spring design problem, finds minimum volume of wire for the production of a coil compression spring. Using special ordered sets. Source: E. Sangren, "Nonlinear Integer and Discrete Programming in Mechanical Design Optimization", Trans. ASME, J. Mech. Design 112, 223-229, 1990.

stockcycle Pure integer NLP which minimizes totall average stock cycle. Source: "A fast heuristic for minimizing total average cycle stock subject to practical constraints", E.A. Silver & I. Moon, JORS 50, 789-796, August 1999. Model uses SOS to express discrete variables.

synthes(1-3) Synthesis of processing system. Source: M. Duran & I.E. Grossmann, "An outer approximation algorithm for a class of mixed integer nonlinear programs", Mathematical Programming 36, pp. 307-339, 1986.

top1-(15x05,30x10,60x20) Topology optimization for compliance minimization of statically loaded structures for 15 x 5, 30 x 10 and 60 x 20 finite element grid. Structure of type 1 (see picture).

Source: O. Sigmund, "A 99 line topology optimization code written in Matlab", Technical University of Denmark, October 1999. See also the TopOpt Homepage.

trimlon(2-12) Nonconvex MINLP arising from trim loss minimization in the paper industry. The problem is to produce a set of product paper rolls from raw paper rolls such that a cost function including the trim loss and the overall production cost is minimized.

There are several data files for different sized problems (e.g. trimlon2.dat is for 2 products, trimlon4.dat for 4 etc).

Source: I. Harjunkoski, T. Westerlund, R. P\"{o}rn and H. Skrifvars "Different transformations for solving non--convex trim loss problems by MINLP", European Journal of Operational Research 105 (1998) 594-603.

trimloss(2-12) Convex MINLP arising from trim loss minimization in the paper industry. The problem is to produce a set of product paper rolls from raw paper rolls such that a cost function including the trim loss and the overall production cost is minimized.

There are several data files for different sized problems (e.g. trimloss2.dat is for 2 products, trimloss4.dat for 4 etc).

Source: I. Harjunkoski, T. Westerlund, R. P\"{o}rn and H. Skrifvars "Different transformations for solving non--convex trim loss problems by MINLP", European Journal of Operational Research 105 (1998) 594-603.

wind-fac Model of the winding factor of the electrical machines due to Michal MICHNA, Polytechnika Gdanska, June 2000.

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