Heuristics

An analysis of the operation of differential evolution at high and low crossover rates (2010)

by James Montgomery

IEEE CEC 2010
http://dx.doi.org/10.1109/CEC.2010.5586128

Crossover and the different faces of differential evolution searches (2010)

by James Montgomery

IEEE CEC 2010
http://dx.doi.org/10.1109/CEC.2010.5586184

The Magic or Myth of Expertise: A Comparison of Judgment Processes between Forensic Experts and Lay Persons Based on Psychiatric Case Vignettes.

by Cato Grønnerød

Prepublished online version: Grøndahl, P., Grønnerød, C., & Sexton, J. (2011). The Magic or Myth of Expertise: A Comparison of Judgment Processes between Forensic Experts and Lay Persons Based on Psychiatric Case Vignettes. Psychiatry. Psychology and Law, iFirst article, 2011, 1–10. DOI:10.1080/13218719.2011.615812

As a continuation of a previous study (Grøndahl, Grønnerød, & Sexton, 2009), we examined how 120 laypersons and 35... more As a continuation of a previous study (Grøndahl, Grønnerød, & Sexton, 2009), we examined how 120 laypersons and 35 forensic experts (14 psychiatrists and 21 psychologists) differed in their judgment processes of forensic case vignettes. The vignettes contained descriptions of three components, namely social history, psychiatric history and criminal offense. We found important differences in how the groups used information when they rated insanity, risk and need for treatment. The professional groups emphasized all three case components as opposed to laypersons. As for priming, all the groups rated lower on risk and need for treatment when the case started with a positive description. More professional experience was related to lower insanity and treatment ratings and higher risk ratings. The professionals generally rated less confidence in their judgments compared to the laypersons. Professionals and lay persons thus seem to evaluate forensic material differently.

The “rationality wars” in psychology: Where they are and where they could go.

by Thomas Sturm

Published in:  Inquiry, 55 (2012), 66-81.

Current psychology of human reasoning is divided into several different approaches. For instance, there is a major... more Current psychology of human reasoning is divided into several different approaches. For instance, there is a major dispute over the question whether human beings are able to apply norms of the formal models of rationality such as rules of logic, or probability and decision theory, correctly. While researchers following the “heuristics and biases” approach argue that we deviate systematically from these norms, and so are perhaps deeply irrational, defenders of the “bounded rationality” approach think not only that the evidence for this conclusion is problematic but also that we should not, at least not very often, use formal norms in reasoning. I argue that while the evidence for heuristics and biases is indeed questionable, the bounded rationality approach has its limits too. Most especially, we should not infer that formal norms play no role in a comprehensive theory of rationality. Instead, formal and bounded rules of reasoning might even be connected in a more comprehensive theory of rationality.

OPTIMIZACIÓN HEURÍSTICA MEDIANTE CRISTALIZACIÓN SIMULADA

by Víctor Yepes

A novel hybrid genetic algorithm for the open shop scheduling problem

by Mehdi Hosseinabadi Farahani

International Journal of Advanced Manufacturing Technology
DOI 10.1007/s00170-011-3825-1

In this paper, a hybrid genetic algorithm is proposed for the open shop scheduling problem with the objective of... more In this paper, a hybrid genetic algorithm is proposed for the open shop scheduling problem with the objective of minimizing the makespan. In the proposed algorithm, a specialized crossover operator is used that preserves the relative order of jobs on machines and a strategy is applied to prevent from searching redundant solutions in the mutation operator. Moreover, an iterative optimization heuristic is employed which uses the concept of randomized active schedules, a dispatching index based on the longest remaining processing time rule and a lower bound to further decrease the search space. Computational results show that the proposed algorithm outperforms other genetic algorithms and is very competitive with well-known metaheuristics available in the literature.

The Logic of Explanatory Power

by Jonah N. Schupbach

Co-authored with Jan Sprenger

This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has... more This article introduces and defends a probabilistic measure of the explanatory power that a particular explanans has over its explanandum. To this end, we propose several intuitive, formal conditions of adequacy for an account of explanatory power. Then, we show that these conditions are uniquely satisfied by one particular probabilistic function. We proceed to strengthen the case for this measure of explanatory power by proving several theorems, all of which show that this measure neatly corresponds to our explanatory intuitions. Finally, we briefly describe some promising future projects inspired by our account. (Philosophy of Science (2011) 78(1): 105-127).

Comparing Probabilistic Measures of Explanatory Power

by Jonah N. Schupbach

Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several... more Recently, in attempting to account for explanatory reasoning in probabilistic terms, Bayesians have proposed several measures of the degree to which a hypothesis explains a given set of facts. These candidate measures of "explanatory power" are shown to have interesting normative interpretations and consequences. What has not yet been investigated, however, is whether any of these measures are also descriptive of people’s actual explanatory judgments. Here, I present my own experimental work investigating this question. I argue that one measure in particular is an accurate descriptor of explanatory judgments. Then, I discuss some interesting implications of this result for both the epistemology and the psychology of explanatory reasoning. (Philosophy of Science, Forthcoming).

Studies in the Logic of Explanatory Power

by Jonah N. Schupbach

Human reasoning often involves explanation. In everyday affairs, people reason to hypotheses based on the explanatory... more Human reasoning often involves explanation. In everyday affairs, people reason to hypotheses based on the explanatory power these hypotheses afford; I might, for example, surmise that my toddler has been playing in my office because I judge that this hypothesis delivers a good explanation of the disarranged state of the books on my shelves. But such explanatory reasoning also has relevance far beyond the commonplace. Indeed, explanatory reasoning plays an important role in such varied fields as the sciences, philosophy, theology, medicine, forensics, and law.

This dissertation provides an extended study into the logic of explanatory reasoning via two general questions. First, I approach the question of what exactly we have in mind when we make judgments pertaining to the explanatory power that a hypothesis has over some evidence. This question is important to this study because these are the sorts of judgments that we constantly rely on when we use explanations to reason about the world. Ultimately, I introduce and defend an explication of the concept of explanatory power in the form of a probabilistic measure. This formal explication allows us to articulate precisely some of the various ways in which we might reason explanatorily.

The second question this dissertation examines is whether explanatory reasoning constitutes an epistemically respectable means of gaining knowledge. I defend the following ideas: The probability theory can be used to describe the logic of explanatory reasoning, the normative standard to which such reasoning attains. Explanatory judgments, on the other hand, constitute heuristics that allow us to approximate reasoning in accordance with this logical standard while staying within our human bounds. The most well known model of explanatory reasoning, Inference to the Best Explanation, describes a cogent, nondeductive inference form. And reasoning by Inference to the Best Explanation approximates reasoning directly via the probability theory in the real world. Finally, I respond to some possible objections to my work, and then to some more general, classic criticisms of Inference to the Best Explanation. In the end, this dissertation puts forward a clearer articulation and novel defense of explanatory reasoning. (Successfully defended on June 14, 2011).

Mejoramiento de rutas de distribución de productos para lograr una ventaja competitiva

by Elias Olivares-Benitez

Co-authored with R. Hernández-Díaz, J.L. Martínez Flores, and J.P. Nuño de la Parra

Una ventaja competitiva nace de la realización de varias actividades en las que se lleva a cabo diseño, fabricación,... more Una ventaja competitiva nace de la realización de varias actividades en las que se lleva a cabo diseño, fabricación, comercialización, entrega y apoyo al producto, y todas estas actividades contribuyen a que la posición de la empresa se vea beneficiada cuando se realizan correctamente y se genera una diferenciación. El presente trabajo muestra un modelo para mejorar las rutas de distribución de productos para lograr disminuir los costos de transportación permitiendo a las empresas lograr una ventaja competitiva, sin dejar de lado el mejoramiento del servicio al cliente. Esta situación se modeló como un problema de ruteo periódico de vehículos (PVRP). En este problema las rutas de vehículos deben ser construidas sobre múltiples días, de tal manera que para cada día del período de planeación, una flotilla de vehículos con cierta capacidad viaja a través de las rutas que comienzan y finalizan en un almacén. El objetivo es encontrar un conjunto de rutas para cada vehículo que minimice el costo total de viaje mientras satisface restricciones de operación, tales como capacidad del vehículo y número de visitas. Para resolverlo se usan heurísticas de inserción conocidas tales como el Algoritmo del Vecino más Cercano y principios lean, y se probaron con escenarios de 8, 15, 50, 100, 200 y 500 clientes con resultados satisfactorios.

A competitive advantage stems from the realization of several activities being carried out like design, manufacture, marketing, delivery and product support. These activities contribute to the position of the company, being benefited when done correctly and a differentiation is generated. This work shows a model for improving delivery routes of products to reduce transportation costs by allowing companies to achieve competitive advantage, without leaving aside the improvement of customer service. This problem was modeled as a periodic vehicle routing (PVRP). In this problem the routes of vehicles should determined in multiple days, where for each day of the planning period, a fleet of vehicles with certain capacity travels through the routes beginning and ending in a warehouse. The goal is to find a set of routes for each vehicle that minimizes the total travel cost while meeting operational constraints such as vehicle capacity and number of visits. Known insertion heuristics like Nearest Neighbor Algorithm and lean principles are used to solve scenarios with 8, 15, 50, 100, 200 and
500 clients with satisfactory results.

Heurística de segmentación de nodos para un modelo de distribución a través de una flota heterogénea

by Elias Olivares-Benitez

Co-authored with M.P.G. Acosta, C.R. Navarro, J.L. Martinez, and A.A. Naranjo

En este trabajo se presenta el modelo para un problema de rutas de distribución con flota heterogénea considerando... more En este trabajo se presenta el modelo para un problema de rutas de distribución con flota heterogénea considerando restricciones de peso y volumen para diferentes instancias. Debido a la complejidad para encontrar la solución del modelo, se desarrolló una heurística de segmentación de nodos que permite conformar regiones bajo tres criterios: aislamiento, alejamiento y distancia al almacén, considerando que el número de nodos de cada segmento estén equilibrados. Cada región se resuelve de manera óptima usando software comercial de optimización con el modelo de flota heterogénea que determina el tamaño de la flota y la ruta que debe seguir cada vehículo. Se presentan los resultados para cada instancia y se compara el número de rutas, capacidad utilizada de los vehículos y el tiempo de solución.

This work presents a heterogeneous fleet vehicle routing problem that considers weight and volume constraints for several instances. Because of the complexity to find the optimal solution of the model, a segmentation heuristic was developed to create regions of nodes under three criteria: isolation, separation, and distance to the depot,
considering a similar number of nodes in each region. Each region is solved optimally with commercial optimization software with the
heterogeneous fleet model to determine the size of the fleet and the route for each vehicle. The results for each instance compare the number of routes, the capacity used in the vehicles, and the solution time.

Un caso logístico del problema de ruteo vehicular múltiple m-VRP resuelto con la heurística de Fisher & Jaikumar.

by Elias Olivares-Benitez

Co-authored with A. Guerrero-Campanur and R.E. Pérez-Loaiza

La heurística de asignación generalizada de Fisher & Jaikumar utilizada en el presente proyecto pertenece a los... more La heurística de asignación generalizada de Fisher & Jaikumar utilizada en el presente proyecto pertenece a los métodos de dos fases bajo la secuencia cluster first – route second, y se aplicó en un caso logístico del problema de ruteo vehicular múltiple (m-VRP) dentro de una empresa clasificada como PyME (pequeña y mediana empresa) dedicada a la distribución de productos de papelería y oficina, en el cual m-vehículos parten a visitar a n-clientes y regresan a un mismo centro de distribución, deseando que el tour minimice los costos de transporte respetando la capacidad de cada uno de los m-vehículos así como la demanda del cliente.

The generalized assignment heuristic of Fisher & Jaikumar used in this project belongs to the methods of two phases of the type cluster first – route second, that was applied in a case of the multiple vehicle routing problem (m-VRP) in a SME (small and medium enterprises) company engaged in the distribution of office products, in which m-vehicles visit n-customers and return to the same distribution center, expecting that the tour minimizes the transportation costs meeting the capacity of each of the m-vehicles and the customer demand.

CO2 Optimization of Reinforced Concrete Cantilever Retaining Walls

by Víctor Yepes

Generalized adaptive pursuit algorithm for genetic pareto local search algorithms

by Madalina Drugan

Rational vs. heuristic motives. What matters when redeeming the pledge?

by Kristiano Raccanello

Pawnbroking activity belongs to the secured loan market and in Mexico almost 90% of items pledged are personal or... more Pawnbroking activity belongs to the secured loan market and in Mexico almost 90% of items pledged are personal or family jewels. The valuation of the collateral may differ between the parties involved in the pawn contract because the borrower, besides the economic value, may feel some attachment to the pledge entailing an affective value, but the loan is a function of only the economic value of the pledge. In this paper we test the hypothesis that if the emotions evoked by the pledge guide individual behavior, then the heuristic aspect, but not the rational motive, should be associated with higher likelihood of redeeming it. Besides showing that economic variables are related to the outcome of the pawning process, our model estimations confirm the hypothesis that the individual’s behavior is guided by heuristic but not rational motive.

An application of rule-based forecasting to a situation lacking domain knowledge

by J Armstrong

Co-authored with Monica Adya, Fred Collopy and Miles Kennedy.

Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining... more Rule-based forecasting (RBF) uses rules to combine forecasts from simple extrapolation methods. Weights for combining the rules use statistical and domain-based features of time series. RBF was originally developed, tested, and validated only on annual data. For the M3-Competition, three major modifications were made to RBF. First, due to the absence of much in the way of domain knowledge, we prepared the forecasts under the assumption that no domain knowledge was available. This removes what we believe is one of RBF's primary advantages. We had to re-calibrate some of the rules relating to causal forces to allow for this lack of domain knowledge. Second, automatic identification procedures were used for six time-series features that had previously been identified using judgment. This was done to reduce cost and improve reliability. Third, we simplified the rule-base by removing one method from the four that were used in the original implementation. Although this resulted in some loss in accuracy, it reduced the number of rules in the rule-base from 99 to 64. This version of RBF still benefits from the use of prior findings on extrapolation, so we expected that it would be substantially more accurate than the random walk and somewhat more accurate than equal weights combining. Because most of the previous work on RBF was done using annual data, we especially expected it to perform well with annual data.

How (Far) Can Rationality Be Naturalized?

by Thomas Sturm

Co-authored with Gerd Gigerenzer. Published in: Synthese, 2011 (Online first version).

The paper shows how an empirical study of fast and frugal heuristics can provide norms of good reasoning, and so how... more The paper shows how an empirical study of fast and frugal heuristics can provide norms of good reasoning, and so how (and how far) rationality can be naturalized. We explain the heuristics humans often rely on in solving problems, such as choosing investment strategies or apartments, placing bets in sports, or making library searches. After that, we show that heuristics can lead to judgments that are as accurate as or even more accurate than strategies that use more information and computation, including optimization methods. A standard way to defend the use of heuristics is by reference to accuracy-effort trade-offs. We take a different route: One can take into account the relation between a reasoner’s heuristics and his environment and argue that, in uncertain environments, more information and computation are not always better (the “less-can-be-more” doctrine). The resulting naturalism about rationality is thus normative because it is ecological. While we desist from claiming that it is unlimited, we think it is of wide practical use.

Finding Shortest Paths Under Time-Bandwidth Constraints by Using Elliptical Minimal Search Area

by Lee D. Han

Transportation Research Record (2006) 1977:225-233
with Hui WANG and William MACKEY

Although many studies on shortest-path algorithms have been conducted, few of them have taken advantage of the added... more Although many studies on shortest-path algorithms have been conducted, few of them have taken advantage of the added characteristics of highway networks and, thus, have failed to become more efficient in finding shortest paths, or lowest-cost paths, for transportation problems. A new concept is proposed for enhancing most existing shortest-path algorithms. Taking advantage of the geographical nature of most transportation networks, the new concept uses a minimal search area to reduce the amount of computations that must be performed by existing algorithms. To simplify the analysis, a hypothetical network in an L1 metric was used to approximate two-dimensional roadways. Empirical results from thousands of shortest paths between arbitrary origin–destination pairs suggested that an elliptical shape is most suitable for confining the search area when seeking a shortest path. Further analysis established the formulation of the ellipse, which becomes rounder when the origin is close to the destination and more elongated when the two points are far apart. The elliptical minimal search area is stable and has a high level of confidence in containing the true shortest path, even if the cost function for each link is dynamic or stochastic. A list of future tasks is presented to further the promising findings of this research. The algorithm, which is not in itself a shortest algorithm per se, can enhance other shortest-path algorithms for transportation roadway networks.

Path-guided mutation for stochastic pareto local search algorithms

by Madalina Drugan

Design of reinforced concrete road vaults by heuristic optimization

by Víctor Yepes