On the MTO production operations inspired by the pursuit-evasion game

2020 ◽  
pp. 2150085
Author(s):  
Fan Wang ◽  
Jia-Jun Li ◽  
Peng-Ju He ◽  
Ying Xue
Keyword(s):  
Decision Making ◽  
Energy Cost ◽  
Optimal Strategy ◽  
Theoretical Work ◽  
Natural Behavior ◽  
Pursuit Evasion ◽  
Make To Order ◽  
Evasion Game ◽  
Rush Order ◽  
The Cost

In the present work, we performed a theoretical work to investigate how a make-to-order (MTO) company operates its producing plan for dealing with a rush-order-inserting problem. Firstly, we constructed two models, the time-minimized and cost-minimized model, to investigate the energy-cost generated by the prey during experiencing the pursuit-evasion game. Inspired by the natural pursuit-evasion game, two models have been extended and re-constructed to understand the cost of MTO company induced by the rush-order-inserting problem. In particular, the present results revealed that the optimal strategy adopted by the prey and the MTO manager are significantly coincident. This work provides helpful findings for operating the rush-order-inserting problem and indicates the natural behavior can be appropriately adopted to guide the manager’s decision making.

scholarly journals An Improved Approach towards Multi-Agent Pursuit–Evasion Game Decision-Making Using Deep Reinforcement Learning

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1433
Author(s):  
Kaifang Wan ◽  
Dingwei Wu ◽  
Yiwei Zhai ◽  
Bo Li ◽  
Xiaoguang Gao ◽  
...  
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Superior Performance ◽  
State Variables ◽  
Multi Agent Systems ◽  
Adversarial Learning ◽  
Pursuit Evasion ◽  
Evasion Game ◽  
Multi Agent ◽  
Adversarial Attack

A pursuit–evasion game is a classical maneuver confrontation problem in the multi-agent systems (MASs) domain. An online decision technique based on deep reinforcement learning (DRL) was developed in this paper to address the problem of environment sensing and decision-making in pursuit–evasion games. A control-oriented framework developed from the DRL-based multi-agent deep deterministic policy gradient (MADDPG) algorithm was built to implement multi-agent cooperative decision-making to overcome the limitation of the tedious state variables required for the traditionally complicated modeling process. To address the effects of errors between a model and a real scenario, this paper introduces adversarial disturbances. It also proposes a novel adversarial attack trick and adversarial learning MADDPG (A2-MADDPG) algorithm. By introducing an adversarial attack trick for the agents themselves, uncertainties of the real world are modeled, thereby optimizing robust training. During the training process, adversarial learning was incorporated into our algorithm to preprocess the actions of multiple agents, which enabled them to properly respond to uncertain dynamic changes in MASs. Experimental results verified that the proposed approach provides superior performance and effectiveness for pursuers and evaders, and both can learn the corresponding confrontational strategy during training.

Solution of a Pursuit–Evasion Game Using a Near-Optimal Strategy

2018 ◽  
Vol 41 (4) ◽  
pp. 841-850 ◽  
Author(s):  
Ryan W. Carr ◽  
Richard G. Cobb ◽  
Meir Pachter ◽  
Scott Pierce
Keyword(s):  
Optimal Strategy ◽  
Pursuit Evasion ◽  
Evasion Game

Emotional Choices

2018 ◽  
Author(s):  
Robin Markwica
Keyword(s):  
Decision Making ◽  
Choice Behavior ◽  
Choice Theory ◽  
Cuban Missile Crisis ◽  
Coercive Diplomacy ◽  
The Core ◽  
Present Book ◽  
Action Model ◽  
The Cost ◽  
Dynamic Interplay

In coercive diplomacy, states threaten military action to persuade opponents to change their behavior. The goal is to achieve a target’s compliance without incurring the cost in blood and treasure of military intervention. Coercers typically employ this strategy toward weaker actors, but targets often refuse to submit and the parties enter into war. To explain these puzzling failures of coercive diplomacy, existing accounts generally refer to coercers’ perceived lack of resolve or targets’ social norms and identities. What these approaches either neglect or do not examine systematically is the role that emotions play in these encounters. The present book contends that target leaders’ affective experience can shape their decision-making in significant ways. Drawing on research in psychology and sociology, the study introduces an additional, emotion-based action model besides the traditional logics of consequences and appropriateness. This logic of affect, or emotional choice theory, posits that target leaders’ choice behavior is influenced by the dynamic interplay between their norms, identities, and five key emotions, namely fear, anger, hope, pride, and humiliation. The core of the action model consists of a series of propositions that specify the emotional conditions under which target leaders are likely to accept or reject a coercer’s demands. The book applies the logic of affect to Nikita Khrushchev’s decision-making during the Cuban missile crisis in 1962 and Saddam Hussein’s choice behavior in the Gulf conflict in 1990–91, offering a novel explanation for why coercive diplomacy succeeded in one case but not in the other.

scholarly journals Economic Value of Terminal Aerodrome Forecasts at Incheon Airport, South Korea

2021 ◽  
Vol 13 (12) ◽  
pp. 6965
Author(s):  
In-Gyum Kim ◽  
Hye-Min Kim ◽  
Dae-Geun Lee ◽  
Byunghwan Lim ◽  
Hee-Choon Lee
Keyword(s):  
Decision Making ◽  
South Korea ◽  
Co2 Emissions ◽  
Fuel Efficiency ◽  
Economic Value ◽  
Analysis Data ◽  
Annual Average ◽  
Loss Model ◽  
Total Budget ◽  
The Cost

Meteorological information at an arrival airport is one of the primary variables used to determine refueling of discretionary fuel. This study evaluated the economic value of terminal aerodrome forecasts (TAF), which has not been previously quantitatively analyzed in Korea. The analysis data included 374,716 international flights that arrived at Incheon airport during 2017–2019. A cost–loss model was used for the analysis, which is a methodology to evaluate forecast value by considering the cost and loss that users can expect, considering the decision-making result based on forecast utilization. The value was divided in terms of improving fuel efficiency and reducing CO2 emissions. The results of the analysis indicate that the annual average TAF value for Incheon Airport was approximately 2.2 M–20.1 M USD under two hypothetical rules of refueling of discretionary fuel. This value is up to 26.2% higher than the total budget of 16.3 M USD set for the production of aviation meteorological forecasts by the Korea Meteorological Administration (KMA). Further, it is up to 10 times greater than the 2 M USD spent on aviation meteorological information fees collected by the KMA in 2018.

scholarly journals Predictive pursuit-evasion game control method for approaching space non-cooperative target

2020 ◽  
Vol 53 (2) ◽  
pp. 14882-14887
Author(s):  
Yuan Chai ◽  
Jianjun Luo ◽  
Mingming Wang ◽  
Min Yu
Keyword(s):  
Control Method ◽  
Pursuit Evasion ◽  
Evasion Game

scholarly journals The Analysis of Small Investors’ Demands on a Thermal Insulation System for a Family House: A Case Study

2021 ◽  
Vol 13 (5) ◽  
pp. 2491
Author(s):  
Alena Tažiková ◽  
Zuzana Struková ◽  
Mária Kozlovská
Keyword(s):  
Decision Making ◽  
Thermal Insulation ◽  
Construction Cost ◽  
Environmental Cost ◽  
Multi Criteria Decision Making ◽  
Insulation System ◽  
Insulation Systems ◽  
Small Investors ◽  
The Cost ◽  
Family House

This study deals with small investors’ demands on thermal insulation systems when choosing the most suitable solution for a family house. By 2050, seventy percent of current buildings, including residential buildings, are still expected to be in operation. To reach carbon neutrality, it is necessary to reduce operational energy consumption and thus reduce the related cost of building operations and the cost of the life cycle of buildings. One solution is to adapt envelopes of buildings by proper insulation solutions. To choose an optimal thermal insulation system that will reduce energy consumption of building, it is necessary to consider the environmental cost of insulation materials in addition to the construction cost of the materials. The environmental cost of a material depends on the carbon footprint from the initial origin of the material. This study presents the results of a multi-criteria decision-making analysis, where five different contractors set the evaluation criteria for selection of the optimal thermal insulation system. In their decision-making, they involved the requirements of small investors. The most common requirements were selected: the construction cost, the construction time (represented by the total man-hours), the thermal conductivity coefficient, the diffusion resistance factor, and the reaction to fire. The confidences of the criteria were then determined with the help of the pairwise comparison method. This was followed by multi-criteria decision-making using the method of index coefficients, also known as the method of basic variant. The multi-criteria decision-making included thermal insulation systems based on polystyrene, mineral wool, thermal insulation plaster, and aerogels’ nanotechnology. As a result, it was concluded that, currently, in Slovakia, small investors emphasize the cost of material and the coefficient of thermal conductivity and they do not care as much about the carbon footprint of the material manufacturing, the importance of which is mentioned in this study.

scholarly journals Application of the theory of decision making under risk and uncertainty at modelling of costs

2010 ◽  
Vol 56 (No. 5) ◽  
pp. 201-208 ◽  
Author(s):  
M. Beranová ◽  
D. Martinovičová
Keyword(s):  
Decision Making ◽  
Financial Accounting ◽  
Cost Functions ◽  
Risk And Uncertainty ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Bayesian Theorem ◽  
Long Run ◽  
Short Run ◽  
The Cost

The costs functions are mentioned mostly in the relation to the Break-even Analysis where they are presented in the linear form. But there exist several different types and forms of cost functions. Fist of all, it is necessary to distinguish between the short-run and long-run cost function that are both very important tools of the managerial decision making even if each one is used on a different level of management. Also several methods of estimation of the cost function's parameters are elaborated in the literature. But all these methods are based on the past data taken from the financial accounting while the financial accounting is not able to separate the fixed and variable costs and it is also strongly adjusted to taxation in the many companies. As a tool of the managerial decision making support, the cost functions should provide a vision to the future where many factors of risk and uncertainty influence economic results. Consequently, these random factors should be considered in the construction of cost functions, especially in the long-run. In order to quantify the influences of these risks and uncertainties, the authors submit the application of the Bayesian Theorem.

scholarly journals ANN-Based Decision Making in Station Keeping for Geotechnical Drilling Vessel

2021 ◽  
Vol 9 (6) ◽  
pp. 596
Author(s):  
Murugan Ramasamy ◽  
Mohammed Abdul Hannan ◽  
Yaseen Adnan Ahmed ◽  
Arun Kr Dev
Keyword(s):  
Decision Making ◽  
Water Depth ◽  
Business Models ◽  
Cost Benefit ◽  
Cost Effective ◽  
Station Keeping ◽  
Operational Information ◽  
Effective Option ◽  
The Cost ◽  
Cost Factors

Offshore vessels (OVs) often require precise station-keeping and some vessels, for example, vessels involved in geotechnical drilling, generally use Spread Mooring (SM) or Dynamic Positioning (DP) systems. Most of these vessels are equipped with both systems to cover all ranges of water depths. However, determining which system to use for a particular operational scenario depends on many factors and requires significant balancing in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors for both the SM and DP station-keeping systems. Operational information and cost data are collected for several field operations, and Artificial Neural Networks (ANN) are trained using those data samples. After that, the trained ANN is used to predict the components of cost for any given environmental situation, fieldwork duration and water depth. Later, the total cost is investigated against water depth for both DP and SM systems to determine the most cost-effective option. The results are validated using two operational scenarios for a specific geotechnical vessel. This decision-making algorithm can be further developed by adding up more operational data for various vessels and can be applied in the development of sustainable decision-making business models for OVs operators.

scholarly journals Exploring the Cost Effectiveness of Shared Decision Making for Choosing between Disease-Modifying Drugs for Relapsing-Remitting Multiple Sclerosis in the Netherlands: A State Transition Model

2020 ◽  
Vol 40 (8) ◽  
pp. 1003-1019
Author(s):  
Ingrid E. H. Kremer ◽  
Mickael Hiligsmann ◽  
Josh Carlson ◽  
Marita Zimmermann ◽  
Peter J. Jongen ◽  
...  
Keyword(s):  
Decision Making ◽  
Cost Effectiveness ◽  
Shared Decision Making ◽  
State Transition ◽  
Transition Model ◽  
Shared Decision ◽  
Relapsing Remitting ◽  
State Transition Model ◽  
The Cost ◽  
Relapsing Remitting Multiple Sclerosis

Background Up to 31% of patients with relapsing-remitting multiple sclerosis (RRMS) discontinue treatment with disease-modifying drug (DMD) within the first year, and of the patients who do continue, about 40% are nonadherent. Shared decision making may decrease nonadherence and discontinuation rates, but evidence in the context of RRMS is limited. Shared decision making may, however, come at additional costs. This study aimed to explore the potential cost-effectiveness of shared decision making for RRMS in comparison with usual care, from a (limited) societal perspective over a lifetime. Methods An exploratory economic evaluation was conducted by adapting a previously developed state transition model that evaluates the cost-effectiveness of a range of DMDs for RRMS in comparison with the best supportive care. Three potential effects of shared decision making were explored: 1) a change in the initial DMD chosen, 2) a decrease in the patient’s discontinuation in using the DMD, and 3) an increase in adherence to the DMD. One-way and probabilistic sensitivity analyses of a scenario that combined the 3 effects were conducted. Results Each effect separately and the 3 effects combined resulted in higher quality-adjusted life years (QALYs) and costs due to the increased utilization of DMD. A decrease in discontinuation of DMDs influenced the incremental cost-effectiveness ratio (ICER) most. The combined scenario resulted in an ICER of €17,875 per QALY gained. The ICER was sensitive to changes in several parameters. Conclusion This study suggests that shared decision making for DMDs could potentially be cost-effective, especially if shared decision making would help to decrease treatment discontinuation. Our results, however, may depend on the assumed effects on treatment choice, persistence, and adherence, which are actually largely unknown.

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