The use of heuristics in valuation practice : implications in a changing market

Despite the existence of prescribed frameworks, valuation remains a cause of much controversy and variety of opinion. It does not matter whether procedures are undertaken in exactly the same way, the conclusion of ‘value’ will vary from valuer to valuer – sometimes considerably. This uncertainty within valuation is founded on property’s heterogeneous nature and the imperfect market that is the property market; in addition to the unpredictability of human behaviour in making judgements (French and Gabrielli 2004). Uncertainty, in valuation is found in the amalgam of locational, physical and legal characteristics and innumerable other forces which control and energise the property market (Whipple 1995). Particular irregular occurrences, or drastic changes in property markets, from either within market evolution or external forces, for example the creation of global financial markets, cause further uncertainty for valuers and provides challenges in identifying ‘market value’ in valuation practice. The praxis of valuation in a commercial sense navigates this complexity using a combination of algorithms and heuristics to identify the value of a property. The application of theoretical mathematical algorithms based on economic theory (Brown 1995), is augmented by valuers’ ability to apply appropriate adjustment based on their knowledge of the market, their ability to analyse, assess and compare the attributes of a property in comparison to its market, and their practical experience (Sliogeriene 2008). Despite the necessity of algorithms, the application of appropriate adjustments and assumptions are important in arriving at a value. This paper is a critical reflection on the basis of valuation practice as guided by standards, methods, and ethics (algorithms), and the use of heuristics in practice. This is important because changes within property markets challenge the inter-relationship between these two aspects of valuation practice. Through the authors’ industry experience and a review of previous research and statements of practice norms this paper provides an analysis of the ability of valuers to address market change in their valuation practices.

Modelling interplay in normative social systems: towards a heuristics formalism of agents and networks

The need for guiding model formulation of normative social systems in support of a digital ecosystem is introduced. Normative social systems improve the understanding of computational social processes in simulation and experimentation, and provide support for digital ecosystem developments. However, a successful simulation requires the appropriate implementation of a conceptual model. It is proposed that an heuristic formalism of agents, networks and environments, complements the conventional creative approach to model formulation by guiding the formulation of conceptual models via abstract components and facilitate interface with other components in a digital environment.

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.