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Distributed computing may be looked at from many points of view. Task scheduling is the viewpoint, where a distributed application can be described as a Directed Acyclic Graph and every node of the graph is executed independently. There are, however, data dependencies and the nodes have to be executed in a specified order. Hence the parallelism of the execution is limited. The scheduling problem is difficult and therefore heuristics are used. However, many inaccuracies are caused by the model used for the system, in which the heuristics are being tested. In this paper we present a tool for simulating the execution of the distributed application on a "real" computer network, and try to tell how the executionis influenced compared to the model.

AbstractWe consider a generalized one‐dimensional bin‐packing model where the cost of a bin is a nondecreasing concave function of the utilization of the bin. Four popular heuristics from the literature of the classical bin‐packing problem are studied: First Fit (FF), Best Fit (BF), First Fit Decreasing (FFD), and Best Fit Decreasing (BFD). We analyze their worst‐case performances when they are applied to our model. The absolute worst‐case performance ratio of FF and BF is shown to be exactly 2, and that of FFD and BFD is shown to be exactly 1.5. Computational experiments are also conducted to test the performance of these heuristics. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006

Presents an investigation into the existence of information processing heuristics in two commercial bank lender types that provide investment and construction loans secured by real estate. Expert real estate banking lenders and expert private banking lenders evidenced different, systematic group specific heuristic usage. Heuristics constrained information cue relevancy and affected the lending decision. Expert private banking lenders mitigated real estate risk by using non‐collateral specific information cues. Real estate lending experts did not mitigate real estate market risk and required favourable collateral specific information cues in order to approve a loan. Concludes that access to credit for real estate investment may be limited by lender expertise because the development of expertise mandates restrictive task interpretation and cue relevance.

Introduction: The environment that surrounds people is changing, unpredictable and uncertain, so in the use of the neo cerebral cortex, heuristics gain prominence in decision making, which in the business field is important to know the influence of the same in the support seeking successful sales in the commercial sector. This is related to local economies and the circulation of capital, the growth of wealth for the benefit of people. Objectives: To determine if the owners use heuristics to procure sales and observe what they do to enhance the chances of success for the commercialization of the products. Methodology: The study was conducted in a quantitative exploratory manner of a transactional nature through a survey designed with constructs to obtain the data. Results: It was determined that 81.31% of the population chosen in the Cuba neighborhood of the city of Manta uses heuristics as a fundamental tool in decision-making and in application of the heuristic principles of representativeness, availability, adjustment, and anchoring given that 76.77% of the owners improve the situation by having formal education. Conclusions: The owners do use heuristics, consciously or not, in an effort to sustain the operation of their businesses. At the same time, it was possible to observe that the behaviors obtained are of a fractal nature, which leads to continue exploring new polygons and that better strategies are determined to promote local economies based on trade, useful information for educational institutions, local governments, and private entrepreneurs. ; Introducción: El entorno que rodea a las personas es cambiante, impredecible e incierto por lo que en uso del neocórtex cerebral la heurística gana protagonismo en la toma de decisiones lo cual en el ámbito de negocios es importante conocer la influencia de este en el sostenimiento procurando ventas exitosas en el sector comercial. Esto se relaciona de forma directa con las economías locales y la circulación de capital, el crecimiento de la riqueza a beneficio ...

Intro -- Preface -- Contents -- About the Author -- Part I Foundations -- 1 Introduction to Stochastic Optimisation -- 1.1 Introduction -- 1.2 Conventional Optimisation Methods -- 1.3 Modern Stochastic Methods -- 1.3.1 Heuristics -- 1.3.2 Meta-Heuristics -- 1.3.3 No Free Lunch Theorems -- 1.3.4 Evolutionary Algorithms (EAs) -- 1.3.5 Swarm Intelligence (SI) -- 1.3.6 Socio-inspired Algorithms -- 1.3.7 Physics Inspired Algorithms -- 1.3.8 Hyper-Heuristics -- 1.4 Summary -- References -- 2 Introduction to Culture -- 2.1 Introduction -- 2.2 What is the Culture? -- 2.3 Characteristic Features of Culture -- 2.4 Cultural Learning in Humans and Animals -- 2.5 Cultural Evolution -- 2.6 Social Learning Biases -- 2.7 Who Can Change Cultural Variants? -- 2.8 Summary -- References -- 3 Cultural Algorithms (CAs) -- 3.1 Introduction -- 3.2 Overall Framework -- 3.3 Population Space -- 3.4 Belief Space -- 3.4.1 Situational Knowledge -- 3.4.2 Normative Knowledge -- 3.4.3 History Knowledge -- 3.4.4 Topographical Knowledge -- 3.4.5 Domain Knowledge -- 3.5 Communication Protocols -- 3.5.1 Acceptance Function -- 3.5.2 Influence Function -- 3.6 Cultural Adjustment -- 3.7 Algorithmic Steps -- 3.8 Illustrative Example -- 3.9 Summary -- References -- Part II Application of Cultural Algorithms -- 4 Applications of Cultural Algorithms in Engineering -- 4.1 Introduction -- 4.2 Civil Engineering -- 4.2.1 Transportation Engineering -- 4.2.2 Structural Engineering -- 4.2.3 Environmental Engineering -- 4.2.4 Urban Engineering -- 4.2.5 Water Engineering -- 4.3 Mechanical Engineering -- 4.3.1 Damage Detection -- 4.3.2 Optimum Design -- 4.3.3 Composite Structures -- 4.3.4 Optimal Vibration Control -- 4.3.5 Vehicle Safety -- 4.3.6 Flight Control -- 4.3.7 Gas Turbine Operation -- 4.3.8 Renewable Energy -- 4.4 Chemical Engineering -- 4.4.1 Penicillin Production.

AbstractOver the past decades psychological theories have made significant headway into economics, culminating in the 2002 (partially) and 2017 Nobel prizes awarded for work in the field of Behavioral Economics. Many of the insights imported from psychology into economics share a common trait: the presumption that decision makers use shortcuts that lead to deviations from rational behaviour (the Heuristics-and-Biases program). Many economists seem unaware that this viewpoint has long been contested in cognitive psychology. Proponents of an alternative program (the Ecological-Rationality program) argue that heuristics need not be irrational, particularly when judged relative to characteristics of the environment. We sketch out the historical context of the antagonism between these two research programs and then review more recent work in the Ecological-Rationality tradition. While the heuristics-and-biases program is now well-established in (mainstream neo-classical) economics via Behavioral Economics, we show there is considerable scope for the Ecological-Rationality program to interact with economics. In fact, we argue that there are many existing, yet overlooked, bridges between the two, based on independently derived research in economics that can be construed as being aligned with the tradition of the Ecological-Rationality program. We close the paper with a discussion of the open challenges and difficulties of integrating the Ecological Rationality program with economics.

Purpose
This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies.


Design/methodology/approach
Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 vertices, as well as 9 asymmetric instances ranging in size from 17 to 443 vertices.


Findings
The results demonstrate the GT is the fastest method for preventing subtours for instances below 400 vertices. Additionally, a distinction between fragment constructive heuristics and the subtour elimination methodology used to ensure the feasibility of resulting solutions enables the introduction of a new vertex-greedy fragment heuristic called ordered greedy.


Originality/value
This research has two main contributions: first, it introduces a novel subtour elimination methodology. Second, the research introduces the concept of ordered lists which remaps the TSP into a new space with promising initial computational results.

Despite the recent increased attention civic education has received, there is little research on the ways that civic leaders problem solve. Such information would be helpful to teachers as they engage students in problem-based learning models of civic education such as classroom-based deliberations and debate and community-based action civics projects. This study explores the civic thinking heuristics civic leaders use when pre-planning action. Across eight think-aloud protocols, findings suggest that three heuristics are employed. Frame alignment refers to the process of harmonizing personal beliefs and interests with the particulars of a civic action issue to find personal meaning in the work. Participants used (1) personal beliefs, (2) lived experiences, (3) their professional roles, and (4) their heritage to facilitate such framing. Referencing is the process of using past personal and historical civic action experiences as case studies for planning. Contextualization is the process of situating a civic issue within a community's political and cultural climate. These three heuristics are sense-making activities that could be taught to and used by students to make sense of civic issues and possible actions available to them. Implications include the need for increased focus on the historical dimensions and personal relevance of civic action.

AbstractMany logistics systems operate in a decentralized way, while most optimization models assume a centralized planner. One example of a decentralized system is in some sea cargo companies: sales agents, who share ship capacity on a network, independently accept cargo from their location and contribute to the revenue of the system. The central headquarters does not directly control the agents' decisions but can influence them through system design and incentives. In this paper, we model the firm's problem to determine the best capacity allocation to the agents such that system revenue is maximized. In the special case of a single‐route, we formulate the problem as a mixed integer program incorporating the optimal agent behavior. For the NP‐hard multiple‐route case, we propose several heuristics for the problem. Computational experiments show that the decentralized system generally performs worse when network capacity is tight and that the heuristics perform reasonably well. We show that the decentralized system may perform arbitrarily worse than the centralized system when the number of locations goes to infinity, although the choice of sales incentive impacts the performance. We develop an upper bound for the decentralized system, where the bound gives insight on the performance of the heuristics in large systems. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007

"Advice, Decision Making, and Leadership in Security Crises" published on by Oxford University Press.