Использование Алгоритма Ускоренного Вероятностного Моделирования в Схеме Табу-Поиска

Рассматривается метаэвристический метод комбинаторной оптимизации, основанный на использовании алгоритмов табу-поиска и ускоренного вероятностного моделирования. Излагается общая вычислительная схема предложенного метода, названного алгоритмом GS-tabu. Приведены результаты серии вычислительных экспериментов по решению известных задач коммивояжера и квадратичных задач о назначении.

Makespan minimization in a job shop with a batch processing machine

A job shop with one batch processing and several discrete machines is analyzed. Given a set of jobs, their process routes, processing requirements, and size, the objective is to schedule the jobs such that the makespan is minimized. The batch processing machine can process a batch of jobs as long as the machine capacity is not violated. The batch processing time is equal to the longest processing job in the batch. The problem under study can be represented as Jm:batch:Cmax. If no batches were formed, the scheduling problem under study reduces to the classical job shop scheduling problem (i.e. Jm:: Cmax), which is known to be NP-hard. This research extends the scheduling literature by combining Jm::Cmax with batch processing. The primary contributions are the mathematical formulation, a new network representation and several solution approaches. The problem under study is observed widely in metal working and other industries, but received limited or no attention due to its complexity. A novel network representation of the problem using disjunctive and conjunctive arcs, and a mathematical formulation are proposed to minimize the makespan. Besides that, several algorithms, like batch forming heuristics, dispatching rules, Modified Shifting Bottleneck, Tabu Search (TS) and Simulated Annealing (SA), were developed and implemented. An experimental study was conducted to evaluate the proposed heuristics, and the results were compared to those from a commercial solver (i.e., CPLEX). TS and SA, with the combination of MWKR-FF as the initial solution, gave the best solutions among all the heuristics proposed. Their results were close to CPLEX; and for some larger instances, with total operations greater than 225, they were competitive in terms of solution quality and runtime. For some larger problem instances, CPLEX was unable to report a feasible solution even after running for several hours. Between SA and the experimental study indicated that SA produced a better average Cmax for all instances. The solution approaches proposed will benefit practitioners to schedule a job shop (with both discrete and batch processing machines) more efficiently. The proposed solution approaches are easier to implement and requires short run times to solve large problem instances.

Entre reglas y excepciones. Es decir, como legitimar las decisiones colectivas

El ensayo examina la cuestión de la aplicación de las reglas y de la capacidad real para tratar casos específicos, llegando a la conclusión de que es la excepción la que confirma la regla, a condición de que sea dialógicamente construida, para que sea interpretable y aplicable por parte de sus numerosos destinatarios en las políticas públicas más complejas y conflictuales, sobre todo a nivel local.

Vivências e manifestações da sexualidade dos idosos em centro de dia

A sexualidade é um processo contínuo e de mudança ao longo da vida, contudo, o comportamento sexual do idoso mantém-se como tema tabu, repleto de estereótipos e falsos mitos. Apesar de pouco discutida, a sexualidade dos idosos constitui uma área emergente para a intervenção dos profissionais de saúde. Diversos estudos apontam para um declínio da função sexual ao longo do ciclo vital, porém, é consensual que os idosos continuam sexualmente ativos. O próprio processo de envelhecimento promove uma transição na atividade sexual, denotando-se uma valorização da componente emocional e relacional, em detrimento da dimensão física. Como objetivo geral deste estudo, pretende-se compreender as vivências e manifestações da sexualidade dos idosos em Centro de dia. Realizou-se um estudo descritivo-exploratório, através de uma abordagem de natureza qualitativa com recurso à investigação fenomenográfica. A entrevista semiestruturada foi a técnica eleita para a colheita de informação, sendo entrevistados dezasseis idosos. Como resultados principais salienta-se que os idosos descrevem a sexualidade numa perspetiva pessoal e tendo em conta as suas vivências, através do conceito de conjugalidade e pela sua narrativa histórica. Na dimensão relacional emerge a complexidade das vivências e da sua historicidade, explicadas pela inibição, experiência positiva, experiência negativa e experiência exploratória. Relativamente às manifestações da sexualidade, elas revelam-se através da erotização e do suporte social. Para a enfermagem, é essencial a compreensão da sexualidade do idoso, permitindo uma comunicação compreensiva e orientada para a realidade e necessidades sexuais vividas, de forma a adequar as intervenções aos problemas individuais

Ilka Quindeau / Micha Brumlik (Hrsg.): Kindliche Sexualität. Weinheim / Basel: Juventa 2012 [Rezension]

Rezension von: Ilka Quindeau / Micha Brumlik (Hrsg.): Kindliche Sexualität, Weinheim / Basel: Juventa 2012 (224 S.; ISBN 978-3-7799-1552-2)

A denúncia de situações de Violência na população portuguesa com 60 ou mais anos

Atualmente a violência contra as pessoas idosas é uma problemática reconhecida em Portugal. Têm sido desenvolvidos estudos (ABUEL e AVOW), nos últimos anos, sobre a sua extensão e natureza, mas permanecem lacunas na literatura, nomeadamente ao nível da procura de ajuda e denúncia por parte das vítimas. É, contudo, consensual que a maior parte das pessoas idosas não denuncia ou procura ajuda quando vivencia uma situação de violência em contexto familiar. No âmbito do estudo de prevalência a nível nacional de violência contra as pessoas idosas em contexto familiar - “Envelhecimento e violência” – apresentam-se alguns dados relativos à denúncia por parte de pessoas com 60+ anos vítimas de violência. O estudo recolheu, através de um inquérito telefónico, dados sobre experiências de violência em contexto familiar a partir de uma amostra aleatória de 1123 indivíduos com 60+ anos a residir em Portugal. Apenas um terço (35%) das vítimas de violência em Portugal denunciou ou apresentou queixa sobre a situação de violência que viveu. Das vítimas que procuraram uma instituição ou serviço, a maioria dirigiu-se a uma força de segurança, como a GNR e a PSP (20%), seguindo-se a rede informal (7%). Dos motivos evocados, pelas pessoas com 60+ anos vítimas de violência, para não denunciarem ou procurarem ajuda, considerar o incidente como irrelevante (38.1%) foi um dos principais, seguindo-se a importância da família e os laços afetivos com o agressor (10.5%). Com menor frequência as vítimas indicaram o medo (de represálias ou de agravar a situação), bem como o medo que ninguém acreditasse (5.9%) e a falta de informação relativa a quem recorrer (5.1%). Estes resultados sugerem que esta problemática permanece ainda como um tabu, com a maior parte das vítimas a vivenciarem em silêncio a violência. As barreiras internas, que se referem ao sistema de crenças da vítima e à dinâmica relacional da vítima com o perpetrador, aparentam ser mais determinantes que as barreiras externas, como serão as dificuldades no acesso e utilização de serviços e respostas sociais.

A graph-based hyper heuristic for timetabling problems

This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Within the hyperheuristic framework, a Tabu Search approach is employed to search for permutations of graph heuristics which are used for constructing timetables in exam and course timetabling problems. This underpins a multi-stage hyper-heuristic where the Tabu Search employs permutations upon a different number of graph heuristics in two stages. We study this graph-based hyper-heuristic approach within the context of exploring fundamental issues concerning the search space of the hyper-heuristic (the heuristic space) and the solution space. Such issues have not been addressed in other hyper-heuristic research. These approaches are tested on both exam and course benchmark timetabling problems and are compared with the fine-tuned bespoke state-of-the-art approaches. The results are within the range of the best results reported in the literature. The approach described here represents a significantly more generally applicable approach than the current state of the art in the literature. Future work will extend this hyper-heuristic framework by employing methodologies which are applicable on a wider range of timetabling and scheduling problems.

Multiple-Retrieval Case-Based Reasoning for Course Timetabling Problems

The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

Hybrid Graph Heuristics within a Hyper-heuristic Approach to Exam Timetabling Problems

This paper is concerned with the hybridization of two graph coloring heuristics (Saturation Degree and Largest Degree), and their application within a hyperheuristic for exam timetabling problems. Hyper-heuristics can be seen as algorithms which intelligently select appropriate algorithms/heuristics for solving a problem. We developed a Tabu Search based hyper-heuristic to search for heuristic lists (of graph heuristics) for solving problems and investigated the heuristic lists found by employing knowledge discovery techniques. Two hybrid approaches (involving Saturation Degree and Largest Degree) including one which employs Case Based Reasoning are presented and discussed. Both the Tabu Search based hyper-heuristic and the hybrid approaches are tested on random and real-world exam timetabling problems. Experimental results are comparable with the best state-of-the-art approaches (as measured against established benchmark problems). The results also demonstrate an increased level of generality in our approach.

Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems

This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are discussed.

Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems

This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual solutions. The heuristic permutations are then used to construct the solutions. Variable Neighborhood Search, Steepest Descent, Iterated Local Search and Tabu Search are compared. An analysis of their performance within the high level search space of heuristics is also carried out. Experimental results on benchmark exam timetabling problems demonstrate the simplicity and efficiency of this hyperheuristic approach. They also indicate that the choice of the high level search methodology is not crucial and the high level search should explore the heuristic search space as widely as possible within a limited searching time. This simple and general graph based hyperheuristic may be applied to a range of timetabling and optimisation problems.

A graph-based hyper heuristic for timetabling problems

This paper presents an investigation of a simple generic hyper-heuristic approach upon a set of widely used constructive heuristics (graph coloring heuristics) in timetabling. Within the hyperheuristic framework, a Tabu Search approach is employed to search for permutations of graph heuristics which are used for constructing timetables in exam and course timetabling problems. This underpins a multi-stage hyper-heuristic where the Tabu Search employs permutations upon a different number of graph heuristics in two stages. We study this graph-based hyper-heuristic approach within the context of exploring fundamental issues concerning the search space of the hyper-heuristic (the heuristic space) and the solution space. Such issues have not been addressed in other hyper-heuristic research. These approaches are tested on both exam and course benchmark timetabling problems and are compared with the fine-tuned bespoke state-of-the-art approaches. The results are within the range of the best results reported in the literature. The approach described here represents a significantly more generally applicable approach than the current state of the art in the literature. Future work will extend this hyper-heuristic framework by employing methodologies which are applicable on a wider range of timetabling and scheduling problems.

Multiple-retrieval case-based reasoning for course timetabling problems

The structured representation of cases by attribute graphs in a Case-Based Reasoning (CBR) system for course timetabling has been the subject of previous research by the authors. In that system, the case base is organised as a decision tree and the retrieval process chooses those cases which are sub attribute graph isomorphic to the new case. The drawback of that approach is that it is not suitable for solving large problems. This paper presents a multiple-retrieval approach that partitions a large problem into small solvable sub-problems by recursively inputting the unsolved part of the graph into the decision tree for retrieval. The adaptation combines the retrieved partial solutions of all the partitioned sub-problems and employs a graph heuristic method to construct the whole solution for the new case. We present a methodology which is not dependant upon problem specific information and which, as such, represents an approach which underpins the goal of building more general timetabling systems. We also explore the question of whether this multiple-retrieval CBR could be an effective initialisation method for local search methods such as Hill Climbing, Tabu Search and Simulated Annealing. Significant results are obtained from a wide range of experiments. An evaluation of the CBR system is presented and the impact of the approach on timetabling research is discussed. We see that the approach does indeed represent an effective initialisation method for these approaches.

Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems

This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual solutions. The heuristic permutations are then used to construct the solutions. Variable Neighborhood Search, Steepest Descent, Iterated Local Search and Tabu Search are compared. An analysis of their performance within the high level search space of heuristics is also carried out. Experimental results on benchmark exam timetabling problems demonstrate the simplicity and efficiency of this hyperheuristic approach. They also indicate that the choice of the high level search methodology is not crucial and the high level search should explore the heuristic search space as widely as possible within a limited searching time. This simple and general graph based hyperheuristic may be applied to a range of timetabling and optimisation problems.

Nurse Rostering with Genetic Algorithms

In recent years genetic algorithms have emerged as a useful tool for the heuristic solution of complex discrete optimisation problems. In particular there has been considerable interest in their use in tackling problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle constraints and successful implementations usually require some sort of modification to enable the search to exploit problem specific knowledge in order to overcome this shortcoming. This paper is concerned with the development of a family of genetic algorithms for the solution of a nurse rostering problem at a major UK hospital. The hospital is made up of wards of up to 30 nurses. Each ward has its own group of nurses whose shifts have to be scheduled on a weekly basis. In addition to fulfilling the minimum demand for staff over three daily shifts, nurses’ wishes and qualifications have to be taken into account. The schedules must also be seen to be fair, in that unpopular shifts have to be spread evenly amongst all nurses, and other restrictions, such as team nursing and special conditions for senior staff, have to be satisfied. The basis of the family of genetic algorithms is a classical genetic algorithm consisting of n-point crossover, single-bit mutation and a rank-based selection. The solution space consists of all schedules in which each nurse works the required number of shifts, but the remaining constraints, both hard and soft, are relaxed and penalised in the fitness function. The talk will start with a detailed description of the problem and the initial implementation and will go on to highlight the shortcomings of such an approach, in terms of the key element of balancing feasibility, i.e. covering the demand and work regulations, and quality, as measured by the nurses’ preferences. A series of experiments involving parameter adaptation, niching, intelligent weights, delta coding, local hill climbing, migration and special selection rules will then be outlined and it will be shown how a series of these enhancements were able to eradicate these difficulties. Results based on several months’ real data will be used to measure the impact of each modification, and to show that the final algorithm is able to compete with a tabu search approach currently employed at the hospital. The talk will conclude with some observations as to the overall quality of this approach to this and similar problems.