Miguel Constantino

A cutting plane approach to capacitated lot-sizing with start-up costs

We consider a mixed integer model for multi-item single machine production planning, incorporating both start-up costs and machine capacity. The single-item version of this model is studied from the polyhedral point of view and several families of valid inequalities are derived. For some of these inequalities, we give necessary and sufficient facet inducing conditions, and efficient separation algorithms. We use these inequalities in a cutting plane/branch and bound procedure. A set of real life based problems with 5 items and up to 36 periods is solved to optimality.

A New Mixed-Integer Programming Model for Harvest Scheduling Subject to Maximum Area Restrictions

Forest ecosystem management often requires spatially explicit planning because the spatial arrangement of harvests has become a critical economic and environmental concern. Recent research on exact methods has addressed both the design and the solution of forest management problems with constraints on the clearcut size, but where simultaneously harvesting two adjacent stands in the same period does not necessarily exceed the maximum opening size. Two main integer programming approaches have been proposed for this area restriction model. However, both encompass an exponential number of variables or constraints. In this work, we present a new integer programming model with a polynomial number of variables and constraints. Branch and bound is used to solve it. The model was tested with both real and hypothetical forests ranging from 45 to 1,363 polygons. Results show that the proposed models solutions were within or slightly above 1% of the optimal solution and were obtained in a short computation time.

Imposing Connectivity Constraints in Forest Planning Models

Connectivity requirements are a common component of forest planning models, with important examples arising in wildlife habitat protection. In harvest scheduling models, one way of addressing preservation concerns consists of requiring that large contiguous patches of mature forest are maintained. In the context of nature reserve design, it is common practice to select a connected region of forest, as a reserve, in such a way as to maximize the number of species and habitats protected. Although a number of integer programming formulations have been proposed for these forest planning problems, most are impractical in that they fail to solve reasonably sized scheduling instances. We present a new integer programming methodology and test an implementation of it on five medium-sized forest instances publicly available in the Forest Management Optimization Site repository. Our approach allows us to obtain near-optimal solutions for multiple time-period instances in fewer than four hours.

A column generation approach for solving a non-temporal forest harvest model with spatial structure constraints

Abstract We present an integer programming model for a non-temporal forest harvest problem with constraints on the clearcut size and on the total area of old growth patches with a minimum size requirement. The model has a very large number of variables for operationally sized problems which precludes the use of exact solution methods. We propose column generation to solve the linear relaxation of the model and a linear programming rounding heuristic to obtain a solution to the model. Column generation may not solve exactly the linear relaxation because the optimization problems associated with the pricing subproblems are NP -hard. We present heuristics for these subproblems. Computational results for test instances and for a real life instance that corresponds to a large Portuguese forest are reported.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs.

Effective formulation reductions for the quadratic assignment problem

In this paper we study two formulation reductions for the quadratic assignment problem (QAP). In particular we apply these reductions to the well known Adams and Johnson [2] integer linear programming formulation of the QAP. We analyze two cases: In the first case, we study the effect of constraint reduction. In the second case, we study the effect of variable reduction in the case of a sparse cost matrix. Computational experiments with a set of 30 QAPLIB instances, which range from 12 to 32 locations, are presented. The proposed reductions turned out to be very effective.

Description of 2-integer continuous knapsack polyhedra

In this paper we discuss the polyhedral structure of several mixed integer sets involving two integer variables. We show that the number of the corresponding facet-defining inequalities is polynomial on the size of the input data and their coefficients can also be computed in polynomial time using a known algorithm [D. Hirschberg, C. Wong, A polynomial-time algorithm for the knapsack problem with two variables, Journal of the Association for Computing Machinery 23 (1) (1976) 147-154] for the two integer knapsack problem. These mixed integer sets may arise as substructures of more complex mixed integer sets that model the feasible solutions of real application problems. al application problems.

Lifting two-integer knapsack inequalities

In this paper we discuss the derivation of strong valid inequalities for (mixed) integer knapsack sets based on lifting of valid inequalities for basic knapsack sets with two integer variables (and one continuous variable). The basic polyhedra can be described in polynomial time. We use superadditive valid lifting functions in order to obtain sequence independent lifting. Most of these superadditive functions and valid inequalities are not obtained in polynomial time.

A polyhedral approach to a production planning problem

Production planning in manufacturing industries is concerned with the determination of the production quantities (lot sizes) of some items over a time horizon, in order to satisfy the demand with minimum cost, subject to some production constraints.In general, production planning problems become harder when different types of constraints are present, such as capacity constraints, minimum lot sizes, changeover times, among others. Models incorporating some of these constraints yield, in general, NP-hard problems.We consider a single-machine, multi-item lot-sizing problem, with those difficult characteristics. There is a natural mixed integer programming formulation for this problem. However, the bounds given by linear relaxation are in general weak, so solving this problem by LP based branch and bound is inefficient. In order to improve the LP bounds, we strengthen the formulation by adding cutting planes. Several families of valid inequalities for the set of feasible solutions are derived, and the corresponding separation problems are addressed. The result is a branch and cut algorithm, which is able to solve some real life instances with 5 items and up to 36 periods.

A branch-and-price approach for harvest scheduling subject to maximum area restrictions

Recently, research on exact methods has been undertaken to solve forest management problems subject to constraints on the maximum clearcut area by using the area restriction model approach. Three main basic integer programming models for these problems have been discussed in the literature: the so-called cluster, path and bucket formulations. Solving these models via branch-and-bound, where all variables and constraints are used a priori, is adequately suited for real problems of a small to medium size, but is not appropriate for larger problems. In this paper, we describe a branch-and-price approach for the cluster model, and we show that this formulation dominates the bucket model, by completing the results of the dominance relationships between the bounds of the three models. Branch-and-price was tested on real and hypothetical forests ranging from 45 to 2945 stands and temporal horizons ranging from three to twelve periods were employed. Results show that the solutions obtained by the proposed approach stood within 1% of the optimal solution and were achieved in a short computation time. It was found that branch-and-bound was unable to produce solutions for most forests from 850 stands with either eleven or an average number of stands per clearcut greater or equal than eight.