bar-truss-3

bard(1-3)

bard(1-3)m

bilevel(1-3)

bilevel(1-2)m

Formulated in original mixed complementarity format.

bilin

bem-milanc30-(s,l)

b_pn2.mod = Two-branch law, Penalty, 2-norm, Imposed displacement q.

dempe

df1

design-cent-*

Maximize the volume of the parameterized body B(x) contained in a second body G, described by a set of convex inequalities,

maximize volume( B(x) )

subj. to B(x) \subset G

where B(x) is a circle (problem 1), an ellipsoid (problems 2 & 3) and a box (problem 4). The set G is a nonconvex wedge in all cases.

Starting points were generated according to Stein and Still using the following AMPL models, design-init-1.mod, design-init-2.mod, design-init-3.mod, design-init-4.mod.

The solution to Problems 1,2 and 4 can be found here.

Two problems (design-cent-2 and design-cent-3) involve division by design variables, which could be small giving rise to badly scaled constraints. This can be remedied by multiplying through by the denominators. Two new problems are added, design-cent-21 and design-cent-31, which have better scaled constraints.

desilva

ex9.1.(1-10)

ex9.2.(1-9)

gnash1(0-9)

gnash1(0-9)m

Formulated in original mixed complementarity format.

flp2

flp4-(1-4)

gauvin

hakonsen

hs044-i

incid-set(1,2)

The incidence set identification problem of Section 9.4: Aim is to bring the membrane of a surface into contact with the obstacle in a prescribed region whose shape is also to be determined.

There are two different obstacles and 3 discretizations.

incid-set(1,2)c

The incidence set identification problem of Section 9.4: Aim is to bring the membrane of a surface into contact with the obstacle in a prescribed region whose shape is also to be determined.

There are two different obstacles and 3 discretizations.

jr(1-2)

kth(1-3)

liswet1-(050,100,200)

monteiro

monteiroB

Here firm B is the leader (rather than firm A in monteiro).

nash1

outrata(31-34)

pack-comp(1,2)-(8,16,32)

pack-comp(1,2)c-(8,16,32)

pack-comp(1,2)p-(8,16,32)

pack-rig(1-3)-(8,16,32)

Problem

pack-rig(1-3)c-(8,16,32)

Two different obstacles (1,2) are available. The links below show the discretization and obstacle 2 respectively (click on the picture to enlarge).

discretization |
obstacle 2 |

Problem

pack-rig(1,2)p-(8,16,32)

portfl-i-(1-6)

This is almost a sensible problem. Here, ask what vector r of minimum norm perturbations to returns R, gives a solution that is as close as possible to the given solution (obtained by rounding soln to portfl1-6).

Problem has data files portfl1.dat - portfl6.dat with different parameters F & R.

qpec(1-2)

qpec-(100,200)-(1-4)

The matlab program write_qpec.m writes a QPEC generated by QPECgen to an ampl file.

ralph(1-2)

scholtes(1-2)

scholtes3

scholtes4

scholtes5

siouxfls

Click here for a figure of the network.

siouxfls1

Click here for a figure of the network.

scale[1-5]

sl1

stackelberg1

tap-09

Click here for a figure of the network.

tap-15

Click here for a figure of the network.

taxmcp

water-(net,FL)

Click here for a figure of the small network and here for a figure of the large network.

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