scholarly journals Parametric shift from rational to irrational decisions in mice

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nathan A. Schneider ◽  
Benjamin Ballintyn ◽  
Donald Katz ◽  
John Lisman ◽  
Hyun-Jae Pi
Keyword(s):  
Large Reward ◽  
Small Reward ◽  
Optimal Solution ◽  
Task Design ◽  
Costs And Benefits ◽  
Sunk Cost ◽  
Classical View ◽  
Optimal Outcomes ◽  
The Cost ◽  
Economic Choices

AbstractIn the classical view of economic choices, subjects make rational decisions evaluating the costs and benefits of options in order to maximize their overall income. Nonetheless, subjects often fail to reach optimal outcomes. The overt value of an option drives the direction of decisions, but covert factors such as emotion and sensitivity to sunk cost are thought to drive the observed deviations from optimality. Many questions remain to be answered as to (1) which contexts contribute the most to deviation from an optimal solution; and (2) the extent of these effects. In order to tackle these questions, we devised a decision-making task for mice, in which cost and benefit parameters could be independently and flexibly adjusted and for which a tractable optimal solution was known. Comparing mouse behavior with this optimal solution across parameter settings revealed that the factor most strongly contributing to suboptimal performance was the cost parameter. The quantification of sensitivity to sunk cost, a covert factor implicated in our task design, revealed it as another contributor to reduced optimality. In one condition where the large reward option was particularly unattractive and the small reward cost was low, the sensitivity to sunk cost and the cost-led suboptimality almost vanished. In this regime and this regime only, mice could be viewed as close to rational (here, ‘rational’ refers to a state in which an animal makes decisions basing on objective valuation, not covert factors). Taken together, our results suggest that “rationality” is a task-specific construct even in mice.

scholarly journals Parameter-dependent shift from rational to irrational decisions in mice

2019 ◽  
Author(s):  
Nathan A. Schneider ◽  
Benjamin Ballintyn ◽  
Donald Katz ◽  
John Lisman ◽  
Hyun-Jae Pi
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Sunk Cost ◽  
Optimal Outcomes ◽  
Economic Choice ◽  
Economic Decision Making ◽  
Biological Substrates ◽  
The Cost ◽  
Parameter Dependent ◽  
Economic Choices

AbstractIn the classical view of economic choices, subjects make rational decisions evaluating the costs and benefits of options in order to maximize their overall income. Nonetheless, subjects often fail to reach optimal outcomes. The overt value of an option drives the direction of decisions, but covert factors such as emotion and sunk cost are thought to drive the observed deviations from optimality. Many questions remain to be answered as to 1) which contexts contribute the most to deviation from an optimal solution; and 2) the extent of these effects. In order to tackle these questions, we devised a decision-making task for mice, in which cost and benefit parameters could be independently and flexibly adjusted and for which a tractable optimal solution was known. Comparing mouse behavior with this optimal solution across parameter settings revealed that the factor most strongly contributing to suboptimality was the cost parameter. The quantification of sunk cost, a covert factor implicated in our task design, revealed it as another contributor to suboptimality. In one condition where the large reward option was particularly unattractive and the small reward cost was low, the sunk cost effect and the cost-led suboptimality almost vanished. In this regime and this regime only, mice could be viewed as close to rational. Taken together, our findings support a model whereby parallel neural circuits independently activate and modulate multiple valuation algorithms, and suggest that “rationality” is a task-specific construct even in mice.Significant StatementIrrational factors in economic decision-making often cause significant deviation from optimal outcomes. By devising a flexible economic choice behavior for mice and comparing their behavior with an optimal solution, we investigated overt and covert factors that contributed to suboptimal outcomes and quantified the deviation from optimality. This investigation identified regimes where mice could be viewed as rational or irrational depending upon the parameters in the same task. These findings may provide a platform to investigate biological substrates underlying rational and irrational decision factors.

Hostile Takeovers and Anti-takeover Defenses in the Russian Corporate Market

2007 ◽  
pp. 70-84 ◽  
Author(s):  
E. Demidova
Keyword(s):  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Benefit Analysis ◽  
Costs And Benefits ◽  
Hostile Takeovers ◽  
Russian Market ◽  
Takeover Defenses ◽  
The Cost ◽  
European Markets

This article analyzes definitions and the role of hostile takeovers at the Russian and European markets for corporate control. It develops the methodology of assessing the efficiency of anti-takeover defenses adapted to the conditions of the Russian market. The paper uses the cost-benefit analysis, where the costs and benefits of the pre-bid and post-bid defenses are compared.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Costs and Benefits of Autonomous Shipping—A Literature Review

2021 ◽  
Vol 11 (10) ◽  
pp. 4553
Author(s):  
Ewelina Ziajka-Poznańska ◽  
Jakub Montewka
Keyword(s):  
Literature Review ◽  
Business Models ◽  
Financial Models ◽  
State Of The Art ◽  
Costs And Benefits ◽  
Capital Costs ◽  
Research Activities ◽  
Benefit Estimation ◽  
Autonomous Ship ◽  
The Cost

The development of autonomous ship technology is currently in focus worldwide and the literature on this topic is growing. However, an in-depth cost and benefit estimation of such endeavours is in its infancy. With this systematic literature review, we present the state-of-the-art system regarding costs and benefits of the operation of prospective autonomous merchant ships with an objective for identifying contemporary research activities concerning an estimation of operating, voyage, and capital costs in prospective, autonomous shipping and vessel platooning. Additionally, the paper outlines research gaps and the need for more detailed business models for operating autonomous ships. Results reveal that valid financial models of autonomous shipping are lacking and there is significant uncertainty affecting the cost estimates, rendering only a reliable evaluation of specific case studies. The findings of this paper may be found relevant not only by academia, but also organisations considering to undertake a challenge of implementing Maritime Autonomous Surface Ships in their operations.

scholarly journals Inclusion of Hydraulic Controls in Rehabilitation Models of Drainage Networks to Control Floods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 514
Author(s):  
Leonardo Bayas-Jiménez ◽  
F. Javier Martínez-Solano ◽  
Pedro L. Iglesias-Rey ◽  
Daniel Mora-Melia ◽  
Vicente S. Fuertes-Miquel
Keyword(s):  
Genetic Algorithm ◽  
Drainage System ◽  
Optimal Solution ◽  
Hydraulic Control ◽  
Drainage Systems ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Extreme Rain ◽  
Rain Events ◽  
The Cost

A problem for drainage systems managers is the increase in extreme rain events that are increasing in various parts of the world. Their occurrence produces hydraulic overload in the drainage system and consequently floods. Adapting the existing infrastructure to be able to receive extreme rains without generating consequences for cities’ inhabitants has become a necessity. This research shows a new way to improve drainage systems with minimal investment costs, using for this purpose a novel methodology that considers the inclusion of hydraulic control elements in the network, the installation of storm tanks and the replacement of pipes. The presented methodology uses the Storm Water Management Model for the hydraulic analysis of the network and a modified Genetic Algorithm to optimize the network. In this algorithm, called the Pseudo-Genetic Algorithm, the coding of the chromosomes is integral and has been used in previous studies of hydraulic optimization. This work evaluates the cost of the required infrastructure and the damage caused by floods to find the optimal solution. The main conclusion of this study is that the inclusion of hydraulic controls can reduce the cost of network rehabilitation and decrease flood levels.

scholarly journals Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)

2019 ◽  
Vol 11 (9) ◽  
pp. 2571
Author(s):  
Xujing Zhang ◽  
Lichuan Wang ◽  
Yan Chen
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Optimal Solution ◽  
Material Distribution ◽  
Low Carbon ◽  
Nsga Ii ◽  
Management Objectives ◽  
Multi Objective Genetic Algorithm ◽  
Distribution Process ◽  
The Cost

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.

Desire for Attention

1977 ◽  
Vol 11 (3) ◽  
pp. 157-161 ◽  
Author(s):  
A. T. Welford
Keyword(s):  
Social Skills ◽  
Personal Relationships ◽  
Costs And Benefits ◽  
Community Attitudes ◽  
Inhibit Action ◽  
The World ◽  
Inhibitory Feedback ◽  
The Cost ◽  
The Relationship

Seeking of attention appears to be intimately bound up with certain principles of motivation, especially the seeking of observable results of action and of optimum levels of stimulation, variety and challenge, and the relationship between results and the cost of achieving them—a high cost will tend to inhibit action but enhance the value subsequently placed upon what is achieved. These principles can be applied to personal relationships: thus friendship can be regarded as a situation involving facilitative feedback between persons, hostility as involving inhibitory feedback and loneliness as occurring when there is no feedback. Which of these situations occurs appears to depend upon the relationships between the costs and benefits of interaction between the persons concerned. The care of psychiatric or senile patients in the community appears likely to impose demands for attention which are unreasonably severe (“costly”). Any attempt to change community attitudes in the hope of securing greater acceptance of such demands appears to be unrealistic. Substantial benefits could probably be attained in many cases from training in skills, especially social skills, which would enable patients to cope more effectively with the world as it is.

An improved proximal method with quasi-distance for nonconvex multiobjective optimization problem

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Fouzia Amir ◽  
Ali Farajzadeh ◽  
Jehad Alzabut
Keyword(s):  
Multiobjective Optimization ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Convergence Result ◽  
Proximal Method ◽  
Pareto Solution ◽  
Multiobjective Optimization Problems ◽  
Locally Lipschitz ◽  
The Cost ◽  
Constrained Multiobjective Optimization

Abstract Multiobjective optimization is the optimization with several conflicting objective functions. However, it is generally tough to find an optimal solution that satisfies all objectives from a mathematical frame of reference. The main objective of this article is to present an improved proximal method involving quasi-distance for constrained multiobjective optimization problems under the locally Lipschitz condition of the cost function. An instigation to study the proximal method with quasi distances is due to its widespread applications of the quasi distances in computer theory. To study the convergence result, Fritz John’s necessary optimality condition for weak Pareto solution is used. The suitable conditions to guarantee that the cluster points of the generated sequences are Pareto–Clarke critical points are provided.

scholarly journals Managing cost uncertainties in transportation and assignment problems

1998 ◽  
Vol 2 (1) ◽  
pp. 65-104 ◽  
Author(s):  
V. Adlakha ◽  
H. Arsham
Keyword(s):  
Time Lag ◽  
Real Life ◽  
Optimal Solution ◽  
Global Market ◽  
Solution Algorithm ◽  
Assignment Problems ◽  
The Stability ◽  
Order Assignment ◽  
Cost Parameters ◽  
The Cost

In a fast changing global market, a manager is concerned with cost uncertainties of the cost matrix in transportation problems (TP) and assignment problems (AP).A time lag between the development and application of the model could cause cost parameters to assume different values when an optimal assignment is implemented. The manager might wish to determine the responsiveness of the current optimal solution to such uncertainties. A desirable tool is to construct a perturbation set (PS) of cost coeffcients which ensures the stability of an optimal solution under such uncertainties.The widely-used methods of solving the TP and AP are the stepping-stone (SS) method and the Hungarian method, respectively. Both methods fail to provide direct information to construct the needed PS. An added difficulty is that these problems might be highly pivotal degenerate. Therefore, the sensitivity results obtained via the available linear programming (LP) software might be misleading.We propose a unified pivotal solution algorithm for both TP and AP. The algorithm is free of pivotal degeneracy, which may cause cycling, and does not require any extra variables such as slack, surplus, or artificial variables used in dual and primal simplex. The algorithm permits higher-order assignment problems and side-constraints. Computational results comparing the proposed algorithm to the closely-related pivotal solution algorithm, the simplex, via the widely-used pack-age Lindo, are provided. The proposed algorithm has the advantage of being computationally practical, being easy to understand, and providing useful information for managers. The results empower the manager to assess and monitor various types of cost uncertainties encountered in real-life situations. Some illustrative numerical examples are also presented.

scholarly journals A Short Path Quantum Algorithm for Exact Optimization

Quantum ◽  
2018 ◽  
Vol 2 ◽  
pp. 78 ◽  
Author(s):  
M. B. Hastings
Keyword(s):  
Hybrid Algorithm ◽  
Optimal Solution ◽  
Quantum Algorithm ◽  
Low Energy ◽  
Weighted Sum ◽  
Natural Hybrid ◽  
Sum Of Products ◽  
Time Required ◽  
The Cost ◽  
Exact Optimization

We give a quantum algorithm to exactly solve certain problems in combinatorial optimization, including weighted MAX-2-SAT as well as problems where the objective function is a weighted sum of products of Ising variables, all terms of the same degree D; this problem is called weighted MAX-ED-LIN2. We require that the optimal solution be unique for odd D and doubly degenerate for even D; however, we expect that the algorithm still works without this condition and we show how to reduce to the case without this assumption at the cost of an additional overhead. While the time required is still exponential, the algorithm provably outperforms Grover's algorithm assuming a mild condition on the number of low energy states of the target Hamiltonian. The detailed analysis of the runtime dependence on a tradeoff between the number of such states and algorithm speed: fewer such states allows a greater speedup. This leads to a natural hybrid algorithm that finds either an exact or approximate solution.

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