Partitioning a permutation graph: algorithms and an application.

In this paper we discuss the problem of partitioning a permutation graph into cliques of bounded size, and describe a real-life application of this problem encountered at a manufacturing company. We formulate the problem as an integer program, and present two exact algorithms for solving it. The first algorithm is a branch-and-price algorithm based on the integer programming formulation; the second one is an algorithm based on the concept of bounded clique-width. The latter algorithm was motivated by the structure present in the real-life instances. Test results are given, both for real-life instances and randomly generated instances. As far as we are aware, this is the first implementation of an algorithm based on bounded clique-width.Algorithms; Analysis of algorithms; Branch-and-price; Companies; Integer programming; Manufacturing; Real life; Size; Structure;

Fast and robust estimation of the multivariate errors in variables model.

In the multivariate errors in variable models one wishes to retrieve a linear relationship of the form y = ß x + a, where both x and y can be multivariate. The variables y and x are not directly measurable, but observed with measurement error. The classical approach to estimate the multivariate errors in variable model is based on an eigenvector analysis of the joint covariance matrix of the observations. In this paper a projection-pursuit approach is proposed to estimate the unknown parameters. Focus is on projection indices based on half-samples. These will lead to robust estimators, which can be computed using fast algorithms. Consistency of the procedure is shown, without needing to make distributional assumptions on the x-variables. A simulation study gives insight in the robustness and the efficiency of the procedure.Algorithms; Consistency; Covariance; Efficiency; Errors in variables; Estimator; Matrix; Measurement; Model; Models; Multivariate statistics; Principal component analysis; Projection-pursuit; Robust estimation; Robustness; Simulation; Studies; Variables;

Mathematical models for multicontainer loading problems

This paper deals with the problem of a distribution company that has to serve its customers by putting first the products on pallets and then loading the pallets onto trucks. We approach the problem by developing and solving integer linear models. We start with basic models, that include the essential features of the problem, such as respecting the dimensions of the truck, and not exceeding the total weight capacity and the maximum weigh capacity on each axle. Then, we add progressively new conditions to consider the weight and volume of pallet bases and to include other desirable features for the solutions to be useful in practice, such as the position of the center of gravity and the minimization of the number of pallets.The models have been tested on a large set of real instances involving up to 46 trucks and kindly provided to us by a distribution company. The results show that in most cases the optimal solution can be obtained in small running times. Moreover, when optimality cannot be proven, the gap is very small, so we obtain high quality solutions for all the instances that we tested

Partitioning a weighted partial order.

The problem of partitioning a partially ordered set into a minimum number of chains is a well-known problem. In this paper we study a generalization of this problem, where we not only assume that the chains have bounded size, but also that a weight wi is given for each element i in the partial order such that wiOrder; Studies; Size; Lower bounds;

Logic based Benders' decomposition for orthogonal stock cutting problems

We consider the problem of packing a set of rectangular items into a strip of fixed width, without overlapping, using minimum height. Items must be packed with their edges parallel to those of the strip, but rotation by 90\ub0 is allowed. The problem is usually solved through branch-and-bound algorithms. We propose an alternative method, based on Benders' decomposition. The master problem is solved through a new ILP model based on the arc flow formulation, while constraint programming is used to solve the slave problem. The resulting method is hybridized with a state-of-the-art branch-and-bound algorithm. Computational experiments on classical benchmarks from the literature show the effectiveness of the proposed approach. We additionally show that the algorithm can be successfully used to solve relevant related problems, like rectangle packing and pallet loading

Modelling and Optimisation of Space Allocation and layout Problems

This thesis investigates the development of optimisation-based, decision-making frameworks for allocation problems related to manufacturing, warehousing, logistics, and retailing. Since associated costs with these areas constitute significant parts to the overall supply chain cost, mathematical models of enhanced fidelity are required to obtain optimal decisions for i) pallet loading, ii) assortment, and iii) product shelf space, which will be the main research focus of this thesis. For the Manufactures Pallet loading problems (MPLP), novel single- and multi-objective Mixed Integer Linear Programming (MILP) models have been proposed, which generate optimal layouts of improved 2D structure based on a block representation. The approach uses a Complexity Index metric, which aids in comparing 2 pallet layouts that share the same pallet size and number of boxes loaded but with different box arrangements. The proposed algorithm has been tested against available data-sets in literature. In the area of Assortments (optimal 2D packing within given containers) , an iterative MILP algorithm has been developed to provide a diverse set of solutions within pre-specified range of key performance metrics. In addition, a basic software prototype, based on AIMMS platform, has been developed using a user-friendly interface so as to facilitate user interaction with a visual display of the solutions obtained. In Shelf- Space Allocation (SSAP) problem, the relationship between the demand and the retailer shelf space allocated to each item is defined as space elasticity. Most of existing literature considers the problem with stationary demand and fixed space elasticities. In this part of the thesis, a dynamic framework has been proposed to forecast space elasticities based on historical data using standard time-series methodologies. In addition, an optimisation mathematical model has been implemented using the forecasted space elasticities to provide the retailer with optimal shelf space thus resulting into closer match between supply and demand and increased profitability. The applicability and effectiveness of the proposed framework is demonstrated through a number of tests and comparisons against literature data-sets

"Algorithms for some Graph-Theoretical Optimization Problems".

Samenvatting Deze thesis situeert zich in het onderzoeksgebied van operationeel onder zoek. We richten ons op methoden om een aantal graaf-theoretische optima lisatie problemen op te lossen. Allereerst geven we een korte introducti e in lineair en integer programmeren en bespreken we enkele oplossingsme thoden die in deze thesis worden gebruikt. Het vervolg van deze thesis k an grofweg in twee delen worden opgesplitst. In het eerste deel komt het opdelen van een partial order aan bod. In het tweede deel be studeren we de structuur en de connectiviteit van het Internet. Het opsplitsen van een partial order in een zo klein mogelijk aantal cha ins is een welbekend en fundamenteel probleem in het vakgebied van opera tioneel onderzoek. Dilworth (1950) toonde aan dat het probleem polynomia al oplosbaar is en dat het minimum benodigde aantal chains gelijk is aan het aantal elementen in een maximale antichain. We generaliseren dit pr obleem door te stellen dat een chain niet meer dan een gegeven aantal el ementen mag bevatten. We stellen een aantal exacte algoritmen voor om di t probleem op te lossen en passen deze toe op een specifiek probleem bij een productiebedrijf in Nederland. Een interessant resultaat van dit on derzoek is dat we bij de probleem instanties van dit productiebedrijf ee n speciale structuur konden vaststellen, gerelateerd aan het concept van de clique-width van een graaf. Door deze structuur kunnen we aantonen d at het probleem, voor deze speciale instanties, polynomiaal oplosbaar is . Vervolgens behandelen we een tweede generalisatie van het probleem, waar bij we aan elk element van de partial order een gewicht toekennen. Het p robleem wordt dan om alle elementen op te delen in chains zod anig dat de som van de gewichten van de chains minimaal is. Hierbij word t het gewicht van een chain gedefinieerd als het gewicht van het zwaarst e element in de chain. Ook hier geldt de capaciteitsbeperking dat elke c hain ten hoogste een gegeven aantal elementen mag bevatten. We geven een aantal ondergrenzen voor de waarde van de optimale oplossing en we stel len een 2-approximatie algoritme voor. In het tweede deel van deze thesis bestuderen we de structuur en de conn ectiviteit van het Internet. Het Internet is de laatste decennia zeer po pulair geworden en de hoeveelheid data die via het Internet wordt verstu urd is enorm gegroeid. Het is zeer belangrijk dat communicatie die via I nternet verloopt efficiënt, veilig en betrouwbaar is, zeker in een tijd waarin virussen binnen enkele uren enorme computer netwerken kunnen stil leggen. Om de structuur en de connectiviteit van het Internet te bestude ren, modelleren we het Internet als een graaf. Een veel gebruikte manier om de connectiviteit van een graaf te analyseren is door het maximale a antal paden en de minimale sneden de bepalen. Het is welbekend dat deze twee problemen polynomiaal oplosbaar zijn voor gewone grafen, maar voor een Internet-graaf is dat niet het geval. Aangezien de definitie van een pad in de graaf in deze context anders is dan bij normale grafen, zijn beide problemen voor Internet-grafen NP-compleet. We stellen een aantal exacte algoritmen voor om deze problemen op te lossen en vergelijken de resultaten met de resultaten van twee 2-approximatie algoritmes voorgest eld door Erlebach et al. (2005).

A matheuristic approach to the integration of three-dimensional Bin Packing Problem and vehicle routing problem with simultaneous delivery and pickup

This work presents a hybrid approach to solve a distribution problem of a Portuguese company in the automotive industry. The objective is to determine the minimum cost for daily distribution operations, such as collecting and delivering goods to multiple suppliers. Additional constraints are explicitly considered, such as time windows and loading constraints due to the limited capacity of the fleet in terms of weight and volume. An exhaustive review of the state of the art was conducted, presenting different typology schemes from the literature for the pickup and delivery problems in the distribution field. Two mathematical models were integrated within a matheuristic approach. One model reflects the combination of the Vehicle Routing Problem with Simultaneous Delivery and Pickup with the Capacitated Vehicle Routing Problem with Time Windows. The second one aims to pack all the items to be delivered onto the pallets, reflecting a three-dimensional single bin size Bin Packing Problem. Both formulations proposed—a commodity-flow model and a formulation of the Three-Dimensional Packing Problem must be solved within the matheuristic. All the approaches were tested using real instances from data provided by the company. Additional computational experiments using benchmark instances were also performed.This research was funded by national funds through FCT—Fundação para a Ciência e a Tecnologia, under the projects UIDB/00285/2020, UIDB/00319/2020. This work was supported by the Research Unit on Governance, Competitiveness and Public Policies (UIDB/04058/2020) + (UIDP/04058/2020), funded by national funds through the Foundation for Science and Technology, IP. This work was also funded by FEDER in the frame of COMPETE 2020 under the project POCI-01-0247-FEDER-072638

Improved Layout Structure with Complexity Measures for the Manufacturer’s Pallet Loading Problem (MPLP) Using a Block Approach

Purpose: The purpose of this paper is to study the Manufacturers pallet-loading problem (MPLP), by loading identical small boxes onto a rectangle pallet to maximise the pallet utilization percentage while reducing the Complexity of loading. Design/methodology/approach: In this research a Block approach is proposed using a Mixed integer linear programming (MILP) model that generates layouts of an improved structure, which is very effective due to its properties in grouping boxes in a certain orientation along the X and Y axis. Also, a novel complexity index is introduced to compare the complexity for different pallet loading, which have the same pallet size but different box arrangements. Findings: The proposed algorithm has been tested against available data-sets in literature and the complexity measure and graphical layout results clearly demonstrate the superiority of the proposed approach compared with literature Manufacturers pallet-loading problem layouts. Originality/value: This study aids real life manufactures operations when less complex operations are essential to reduce the complexity of pallet loading