The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearization are tight, but hardly exploited within a reasonable computing time because of their size. On the other hand, Kaufman and Broeckx formulation [1] is the smallest of these linearizations, but very wea...

This paper reviews the advances of mixed-integer linear programming (MILP) based approaches for the scheduling of chemical processing systems. We focus on the short-term scheduling of general network represented processes. First, the various mathematical models that have been proposed in the literature are classified mainly based on the time representation. Discrete-time and continuous-time mod...

Synonyms Indices i = orders j = productstock tanks s = products k = components l = component tanks n = event points Sets I = orders Ij = orders which can be performed in productstock tank j Is = orders which order product s J = productstock tanks Ji = productstock tanks which are suitable for performing order i Js = productstock tanks which can store product s N = event points within the time h...

Constraint Programming (CP) users need significant expertise in order to model their problems appropriately, notably to select propagators and search strategies. This puts the brakes on a broader uptake of CP. In this paper, we introduce MICE, a complete Java CP modeler that can use any Mixed Integer Linear Programming (MILP) solver as a solution technique. Our aim is to provide an alternative ...

Reliability is an essential factor in distribution networkt expansion planning. However, standard reliability assessment techniques rely on quantifying the impact of a pre-specified set events service continuity through simulation component outages, one at time. Due to such simulation-based nature, incorporation into network planning has customarily required application heuristic and metaheuris...

We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP and scheduled using CP, and the two are linked via logic-based Benders decomposition. We consider two objectives: minimizing the number of late tasks, and minimizing total tardiness. Our main theoretical contribution is...

Mixed integer linear programming (MILP) is a powerful representation often used to formulate decision-making problems under uncertainty. However, it lacks a natural mechanism to reason about objects, classes of objects, and relations. First-order logic (FOL), on the other hand, excels at reasoning about classes of objects, but lacks a rich representation of uncertainty. While representing propo...

Branch and bound algorithms for Mixed-Integer Linear Programming (MILP) almost universally branch on a single variable to create disjunctions. General linear expressions involving multiple variables are another option for branching disjunctions, but are not used for two main reasons: (i) descendent LPs tend to solve more slowly because of the added constraints, so the overall solution time is i...

A coarse registration method using Mixed Integer Linear Programming (MILP) is described that finds global optimal registration parameter values that are independent of the values of invariant features. We formulate the range image registration problem using MILP. Our algorithm using MILP formulation finds the best balanced optimal registration for robustly aligning two range images with the bes...