Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Non-convex mixed-integer nonlinear programming
T2 - a survey
AU - Burer, S
AU - Letchford, Adam
PY - 2012
Y1 - 2012
N2 - A wide range of problems arising in practical applications can be formulated as Mixed-Integer Nonlinear Programs (MINLPs). For the case in which the objective and constraint functions are convex, some quite effective exact and heuristic algorithms are available. When nonconvexities are present, however, things become much more difficult, since then even the continuous relaxation is a global optimisation problem. We survey the literature on non-convex MINLP, discussing applications, algorithms and software. Special attention is paid to the case in which the objective and constraint functions are quadratic.
AB - A wide range of problems arising in practical applications can be formulated as Mixed-Integer Nonlinear Programs (MINLPs). For the case in which the objective and constraint functions are convex, some quite effective exact and heuristic algorithms are available. When nonconvexities are present, however, things become much more difficult, since then even the continuous relaxation is a global optimisation problem. We survey the literature on non-convex MINLP, discussing applications, algorithms and software. Special attention is paid to the case in which the objective and constraint functions are quadratic.
KW - mixed-integer nonlinear programming
KW - global optimisation
U2 - 10.1016/j.sorms.2012.08.001
DO - 10.1016/j.sorms.2012.08.001
M3 - Journal article
VL - 17
SP - 97
EP - 106
JO - Surveys in Operations Research and Management Science
JF - Surveys in Operations Research and Management Science
SN - 1876-7354
IS - 2
ER -