The Convex Hull Heuristic for Nonlinear 0-1 Programming Problems with Linear Constraints

The Convex Hull Heuristic (CHH) is a heuristic for mixed-integer programming problems with a nonlinear objective function and linear constraints. It is a matheuristic in two ways: it is based on the mathematical programming algorithm called simplicial decomposition, or SD, and at each iteration, one solves a mixed-integer programming problem with a linear objective function … Read more

Risk management for forestry planning under uncertainty in demand and prices.

The forest-harvesting and road-construction planning problem basically consists of managing land designated for timber production and divided into harvest cells. For each time period in the given time horizon one must decide which cells to cut and what access roads to build in order to maximize expected net profit under a risk manageable scheme to … Read more

Dynamic vs. Static Optimization of Crossdocking Operations

To improve operations commonly found in today’s crossdocks, we offer a door assignment optimization tool that will reduce the distance travelled by goods across the crossdock, as well as workload and labor cost. The cross dock door assignment problem (CDAP) minimizes total distance traveled by the goods inside the crossdock where door capacities are limited … Read more

Memory-Aware Parallelized RLT3 for Solving Quadratic Assignment Problems

We present a coarse-grain (outer-loop) parallel implementation of RLT1/2/3 (Level 1, 2, and 3 Reformulation and Linearization Technique—in that order) bound calculations for the QAP within a branch-and-bound procedure. For a search tree node of size S, each RLT3 and RLT2 bound calculation iteration is parallelized S ways, with each of S processors performing O(S5) … Read more

Algorithms for the Cross-dock Door Assignment Problem

In a cross-dock facility, goods are moved by forklift from incoming truck platforms (strip doors) to temporary holding areas and then to outgoing truck platforms (stack doors) or directly from strip doors to stack doors. Costs within the cross-dock may be minimized by appropriate assignment of strip doors to incoming trucks and stack doors to … Read more


The behavior of enumeration-based programs for solving MINLPs depends at least in part on the quality of the bounds on the optimal value and of the feasible solutions found. We consider MINLP problems with linear constraints. The convex hull relaxation (CHR) is a special case of the primal relaxation (Guignard 1994, 2007) that is very … Read more

A new, solvable, primal relaxation for convex nonlinear integer programming problems

The paper describes a new primal relaxation (PR) for computing bounds on nonlinear integer programming (NLIP) problems. It is a natural extension to NLIP problems of the geometric interpretation of Lagrangean relaxation presented by Geoffrion (1974) for linear problems, and it is based on the same assumption that some constraints are complicating and are treated … Read more

Combining QCR and CHR for Convex Quadratic MINLP Problems with Linear Constraints

The convex hull relaxation (CHR) method (Albornoz 1998, Ahlatçıoğlu 2007, Ahlatçıoğlu and Guignard 2010) provides lower bounds and feasible solutions (thus upper bounds) on convex 0-1 nonlinear programming problems with linear constraints. In the quadratic case, these bounds may often be improved by a preprocessing step that adds to the quadratic objective function terms which … Read more

Exact Solution of Emerging Quadratic Assignment Problems

We report on a growing class of assignment problems that are increasingly of interest and very challenging in terms of the difficulty they pose to attempts at exact solution. These problems address economic issues in the location and design of factories, hospitals, depots, transportation hubs and military bases. Others involve improvements in communication network design. … Read more

A Level-3 Reformulation-linearization Technique Based Bound for the Quadratic Assignment Problem

We apply the level-3 Reformulation Linearization Technique (RLT3) to the Quadratic Assignment Problem (QAP). We then present our experience in calculating lower bounds using an essentially new algorithm, based on this RLT3 formulation. This algorithm is not guaranteed to calculate the RLT3 lower bound exactly, but approximates it very closely and reaches it in some … Read more