MaxSAT Evaluation 2021 : Solver and Benchmark Descriptions

Non peer reviewe

Applying Data Mining to Scheduling Courses at a University

Scheduling courses ( timetabling ) at a University is a persistent challenge. Allocating course-sections to prescribed time slots for courses requires advanced quantitative techniques, such as goal programming, and collecting a large amount of multi-criteria data at least six to eight months in advance of a semester. This study takes an alternate approach. It demonstrates the feasibility of applying the principles of data mining. Specifically it uses association rules to evaluate a non-standard ( aberrant ) timetabling pilot study undertaken in one College at a University. The results indicate that 1), inductive methods are indeed applicable, 2), both summary and detailed results can be understood by key decision-makers, and 3), straightforward, repeatable SQL queries can be used as the chief analytical technique on a recurring basis. In addition, this study was one of the first empirical studies to provide an accurate measure of the discernable, but negligible, scheduling exclusionary effects that may impact course availability and diversity negatively

MetroNG: Computer-Aided Scheduling and Collision Detection

In this paper, we propose a formal model of the objects involved in a class of scheduling problems, namely in the classroom scheduling in universities which allow a certain degree of liberty in their curricula. Using the formal model, we present efficient algorithms for the detection of collisions of the involved objects and for the inference of a tree-like navigational structure in an interactive scheduling software allowing a selection of the most descriptive view of the scheduling objects. These algorithms were used in a real-world application called MetroNG; a visual interactive tool that is based on more than 10 years of experience we have in the field. It is currently used by the largest universities and colleges in the Czech Republic. The efficiency and usability of MetroNG suggests that our approach may be applied in many areas where multi-dimensionally structured data are presented in an interactive application

Railway timetabling from an operations research

In this paper we describe Operations Research (OR) models andtechniques that can be used for determining (cyclic) railwaytimetables. We discuss the two aspects of railway timetabling: ($i$)the determination of arrival and departure times of the trains atthe stations and other relevant locations such as junctions andbridges, and ($ii$) the assignment of each train to an appropriateplatform and corresponding inbound and outbound routes in everystation. Moreover, we discuss robustness aspects of bothsubproblems.

Problemas de asignación de recursos humanos a través del problema de asignación multidimensional

149 páginas. Doctorado en Optimización.El problema de asignación de personal aparece en diversas industrias. La asignación eficiente de personal a trabajos, proyectos, herramientas, horarios, entre otros, tiene un impacto directo en términos monetarios para el negocio. El problema de asignación multidimensional (PAM) es la extensión natural del problema de asignación y puede ser utilizado en aplicaciones donde se requiere la asignación de personal. El caso más estudiado de PAM es el problema de asignación en tres dimensiones, sin embargo en años recientes han sido propuestas algunas heurísticas de búsqueda local y algoritmos meméticos para el caso general. En este trabajo de tesis se realiza un estudio profundo de PAM comenzando con un resumen del estado del arte de algoritmos, heurísticas y metaheurísticas para su resolución. Se describen algunos algoritmos y se propone uno nuevo que resuelve instancias de tamaño medio para PAM. Se propone la generalización de las conocidas heurísticas de variación de dimensión como una búsqueda local generalizada que proporciona un nuevo estado del arte de búsquedas locales para PAM. Adicionalmente, se propone un algoritmo memético con una estructura sencilla pero efectiva y que es competitivo con el mejor algoritmo memético conocido para PAM. Finalmente, se presenta un caso particular de problema de asignación de personal: el Problema de Asignación de Horarios (PAH). El PAH considera la asignación de personal a uno, dos o más conjuntos de objetos, por ejemplo puede ser requerida la asignación de profesores a cursos a periodos de tiempo a salones, para determinados grupos de estudiantes. Primero, se presenta el PAH así como una breve descripción de su estado del arte. Luego, se propone una nueva forma de modelar este problema a través de la resolución de PAM y se aplica sobre el PAH en la Universidad Autónoma Metropolitana, unidad Azcapotzalco (UAM-A). Se describen las consideraciones particulares del PAH en la UAM-A y proponemos una nueva solución para éste. Nuestra solución se basa en la resolución de múltiples PA3 a través de los algoritmos y heurísticas propuestos.Personnel assignment problems appear in several industries. The e cient assignment of personnel to jobs, projects, tools, time slots, etcetera, has a direct impact in terms monetary for the business. The Multidimensional Assignment Problem (MAP) is a natural extension of the well-known assignment problem and can be used on applications where the assignment of personnel is required. The most studied case of the MAP is the three dimensional assignment problem, though in recent years some local search heuristics and memetic algorithms have been proposed for the general case. Let X1; : : : ;Xs be a collection of s 3 disjoint sets, consider all combinations that belong to the Cartesian product X = X1 Xs such that each vector x 2 X, where x = (x1; : : : ; xs) with xi 2 Xi 8 1 i s, has associated a weight w(x). A feasible assignment is a collection A = (x1; : : : ; xn) of n vectors if xi k 6= xj k for each i 6= j and 1 k s. The weight of an assignment A is given by w(A) = Pn i=1 w(xi). A MAP in s dimensions is denoted as sAP. The objective of sAP is to nd an assignment of minimal weight. In this thesis we make an in depth study of MAP beginning with the state-ofthe- art algorithms, heuristics, and metaheuristics for solving it. We describe some algorithms and we propose a new one for solving optimally medium size instances of MAP. We propose the generalization of the called dimensionwise variation heuristics for MAP and a new generalized local search heuristic that provides new state-of-theart local searches for MAP. We also propose a new simple memetic algorithm that is competitive against the state-of-the-art memetic algorithm for MAP. In the last part of this thesis, we study a particular case of personnel assignment problem: the School Timetabling Problem (STP). The STP considers the assignment of personnel to other two or more sets, for example the assignment of professors to courses to time slots to rooms can be required. First, we provide a brief description of the state-of-the-art for STP. Then, we introduce a new approach for modeling this problem through the resolution of several MAP and we apply our solution on a real life case of study: STP at the Universidad Autonoma Metropolitana campus Azcapotzalco (UAM-A). We provide the particular aspects for STP at UAM-A and we provide a new solution for this problem. Our approach is based on solving several 3AP considering the introduced model and our proposed techniques.Consejo Mexiquense de Ciencia y Tecnología (Comecyt).Consejo Nacional de Ciencia y Tecnología (México

A general framework of multi-population methods with clustering in undetectable dynamic environments

Copyright @ 2011 IEEETo solve dynamic optimization problems, multiple population methods are used to enhance the population diversity for an algorithm with the aim of maintaining multiple populations in different sub-areas in the fitness landscape. Many experimental studies have shown that locating and tracking multiple relatively good optima rather than a single global optimum is an effective idea in dynamic environments. However, several challenges need to be addressed when multi-population methods are applied, e.g., how to create multiple populations, how to maintain them in different sub-areas, and how to deal with the situation where changes can not be detected or predicted. To address these issues, this paper investigates a hierarchical clustering method to locate and track multiple optima for dynamic optimization problems. To deal with undetectable dynamic environments, this paper applies the random immigrants method without change detection based on a mechanism that can automatically reduce redundant individuals in the search space throughout the run. These methods are implemented into several research areas, including particle swarm optimization, genetic algorithm, and differential evolution. An experimental study is conducted based on the moving peaks benchmark to test the performance with several other algorithms from the literature. The experimental results show the efficiency of the clustering method for locating and tracking multiple optima in comparison with other algorithms based on multi-population methods on the moving peaks benchmark

Principles in Patterns (PiP) : Evaluation of Impact on Business Processes

The innovation and development work conducted under the auspices of the Principles in Patterns (PiP) project is intended to explore and develop new technology-supported approaches to curriculum design, approval and review. An integral component of this innovation is the use of business process analysis and process change techniques - and their instantiation within the C-CAP system (Class and Course Approval Pilot) - in order to improve the efficacy of curriculum approval processes. Improvements to approval process responsiveness and overall process efficacy can assist institutions in better reviewing or updating curriculum designs to enhance pedagogy. Such improvements also assume a greater significance in a globalised HE environment, in which institutions must adapt or create curricula quickly in order to better reflect rapidly changing academic contexts, as well as better responding to the demands of employment marketplaces and the expectations of professional bodies. This is increasingly an issue for disciplines within the sciences and engineering, where new skills or knowledge need to be rapidly embedded in curricula as a response to emerging technological or environmental developments. All of the aforementioned must also be achieved while simultaneously maintaining high standards of academic quality, thus adding a further layer of complexity to the way in which HE institutions engage in "responsive curriculum design" and approval. This strand of the PiP evaluation therefore entails an analysis of the business process techniques used by PiP, their efficacy, and the impact of process changes on the curriculum approval process, as instantiated by C-CAP. More generally the evaluation is a contribution towards a wider understanding of technology-supported process improvement initiatives within curriculum approval and their potential to render such processes more transparent, efficient and effective. Partly owing to limitations in the data required to facilitate comparative analyses, this evaluation adopts a mixed approach, making use of qualitative and quantitative methods as well as theoretical techniques. These approaches combined enable a comparative evaluation of the curriculum approval process under the "new state" (i.e. using C-CAP) and under the "previous state". This report summarises the methodology used to enable comparative evaluation and presents an analysis and discussion of the results. As the report will explain, the impact of C-CAP and its ability to support improvements in process and document management has resulted in the resolution of numerous process failings. C-CAP has also demonstrated potential for improvements in approval process cycle time, process reliability, process visibility, process automation, process parallelism and a reduction in transition delays within the approval process, thus contributing to considerable process efficiencies; although it is acknowledged that enhancements and redesign may be required to take advantage of C-CAP's potential. Other aspects pertaining to C-CAP's impact on process change, improvements to document management and the curation of curriculum designs will also be discussed