Relax and fix heuristics to solve one-stage one-machine lot-scheduling models for small-scale soft drink plants

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simple heuristics for the assembly line worker assignment and balancing problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: A comparison study

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

A review and evaluation on constructive heuristics to optimise product mix based on the Theory of Constraints

In this paper, we address the problem of defining the product mix in order to maximise a system's throughput. This problem is well known for being NP-Complete and therefore, most contributions to the topic focus on developing heuristics that are able to obtain good solutions for the problem in a short CPU time. In particular, constructive heuristics are available for the problem such as that by Fredendall and Lea, and by Aryanezhad and Komijan. We propose a new constructive heuristic based on the Theory of Constraints and the Knapsack Problem. The computational results indicate that the proposed heuristic yields better results than the existing heuristic.

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the well-known simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.

Heuristics for minimizing the maximum within-clusters distance

The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at finding a clustering with a predefined number of clusters that minimizes the largest within-cluster distance (diameter) among all clusters. There are two main objectives in this paper: to propose heuristics for the MMD and to evaluate the suitability of the best proposed heuristic results according to the real classification of some data sets. Regarding the first objective, the results obtained in the experiments indicate a good performance of the best proposed heuristic that outperformed the Complete Linkage algorithm (the most used method from the literature for this problem). Nevertheless, regarding the suitability of the results according to the real classification of the data sets, the proposed heuristic achieved better quality results than C-Means algorithm, but worse than Complete Linkage.

Essays in structural heuristics

This dissertation introduces and develops a new method of rational reconstruction called structural heuristics. Structural heuristics takes assignment of structure to any given object of investigation as the starting point for its rational reconstruction. This means to look at any given object as a system of relations and of transformation laws for those relations. The operational content of this heuristics can be summarized as follows: when facing any given system the best way to approach it is to explicitly look for a possible structure of it. The utilization of structural heuristics allows structural awareness, which is considered a fundamental epistemic disposition, as well as a fundamental condition for the rational reconstruction of systems of knowledge. In this dissertation, structural heuristics is applied to reconstructing the domain of economic knowledge. This is done by exploring four distinct areas of economic research: (i) economic axiomatics; (ii) realism in economics; (iii) production theory; (iv) economic psychology. The application of structural heuristics to these fields of economic inquiry shows the flexibility and potential of structural heuristics as epistemic tool for theoretical exploration and reconstruction.

The loss of trust in the European Union during the great recession since 2007: The role of heuristics from the national political system

How can we explain the decline in support for the European Union (EU) and the idea of European integration after the onset of the great recession in the fall of 2007? Did the economic crisis and the austerity policies that the EU imposed—in tandem with the IMF—on several member countries help cause this drop? While there is some evidence for this direct effect of EU policies, we find that the most significant determinant of trust and support for the EU remains the level of trust in national governments. Based on cue theory and using concepts of diffuse and specific support, we find that support for the EU is derived from evaluations of national politics and policy, which Europeans know far better than the remote political system of the EU. This effect, however, is somewhat muted for those sophisticated Europeans that are more knowledgeable about the EU and are able to form opinions about it independently of the national contexts in which they live. We also find that the recent economic crisis has led to a discernible increase in the number of those who are disillusioned with politics both at the national and the supranational level. We analyze 133 national surveys from 27 EU countries by estimating a series of cross-classified multilevel logistic regression models.

Heuristics that dynamically alter data structures to decrease their access time /

Vita.

Computer based approaches to managerial decision making:optimism, heuristics and simulation

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Classifying clinical decision making:interpreting nursing intuition, heuristics and medical diagnosis

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.