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 …

In this paper, we examine a mixed integer linear programming reformulation for mixed
integer bilinear problems where each bilinearterm involves the product of a nonnegative …

Abstract The Feasibility Pump (fp) is probably the best-known primal heuristic for mixed-
integer programming. The original work by Fischetti et al.(Math Program 104 (1): 91–104 …

In the literature for mixed integer programming, heuristic algorithms (particularly primal
heuristics) are often considered as stand-alone procedures; in that context, heuristics are …

This article introduces rens, the relaxation enforced neighborhood search, a large
neighborhood search algorithm for mixed integer nonlinear programs (MINLPs). It uses a …

One of the foremost difficulties in solving Mixed-Integer Nonlinear Programs, either with
exact or heuristic methods, is to find a feasible point. We address this issue with a new …

Feasibility pumps are highly effective primal heuristics for mixed-integer linear and nonlinear
optimization. However, despite their success in practice there are only a few works …

In this paper the application of projection neural network for solving bilinear programming
problems (BLPs) is obtained. So far as we know, no study has yet been attempted for these …

The short-term Unit Commitment (UC) problem in hydro-thermal power generation is a
fundamental problem in short-term electrical generation scheduling. Historically, Lagrangian …

We present Undercover, a primal heuristic for nonconvex mixed-integer nonlinear programs
(MINLPs) that explores a mixed-integer linear subproblem (sub-MIP) of a given MINLP. We …