Reconciling Co-Evolving Engineering and Customer Requirements With a Looped Bayesian Model

2019 ◽  
Author(s):  
Christopher Slon ◽  
Vijitashwa Pandey
Keyword(s):  
Utility Function ◽  
Real Life ◽  
Decision Makers ◽  
Shape Parameters ◽  
Automotive Manufacturing ◽  
Customer Preferences ◽  
Deterministic Function ◽  
State Of Mind ◽  
Utility Distribution ◽  
Decision Based Design

Abstract Engineering and manufacturing abilities of firms evolve with every passing year and so do the preferences of the customers buying their products. Reconciling this coevolution is essential to staying competitive in the marketplace. In this paper, we provide a looped Bayesian framework to accomplish this so that designs can evolve as engineering capabilities increase and customer preferences change. We begin with an approach to incorporating the voice of the customer through the multi-attribute utility function, the core of decision-based design. We consider the utility to be a stochastic function governed by shape parameters that are random variables. Typically, a representative preference or utility function is used or the function is aggregated over many decision makers and regarded as a deterministic function of specified shape parameters. In our approach, the shape parameters represent the stochastic nature of preference behavior either due to variation in a decision maker’s state of mind from one decision to another, or due to a multiplicity of decision makers. The novelty of this approach is in taking a Bayesian perspective on the stochastic utility function. We consider the utility distribution in the design phase as a prior distribution and we update the prior to a posterior with feedback on the actual product in production. The method is valuable in providing a means to improve the level of informativeness of the design level utility function for adjustments to the design or for the next design revision in the cycle of continuous improvement. We present our approach on a real-life assembly problem in an automotive manufacturing floor.

Enabling Decision-Based Design Using Solution Trajectory Correction and Backtracking Rules

2012 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Zissimos P. Mourelatos ◽  
Monica Majcher
Keyword(s):  
Optimal Design ◽  
Utility Function ◽  
Design Space ◽  
A Priori ◽  
Preference Order ◽  
Beam Design ◽  
Effective Decision ◽  
Suboptimal Design ◽  
Trajectory Correction ◽  
Decision Based Design

Optimization is needed for effective decision based design (DBD). However, a utility function assessed a priori in DBD does not usually capture the preferences of the decision maker over the entire design space. As a result, when the optimizer searches for the optimal design, it traverses (or ends up) in regions where the preference order among different solutions is different from the actual order. For a highly non-convex design space, this can lead to convergence to a grossly suboptimal design depending on the initial design. In this article, we propose two approaches to alleviate this issue. First, we map the trajectory of the solution as generated by the optimizer and generate ranking questions that are presented to the designer to verify the correctness of the utility function. We then propose backtracking rules if a local utility function is very different from the initially assessed function. We demonstrate our methodology using a mathematical example and a welded beam design problem.

Optimal fuzzy scheduling and sequencing of multiple-period operating room

2017 ◽  
Vol 32 (1) ◽  
pp. 108-121 ◽  
Author(s):  
Abbas Al-Refaie ◽  
Mays Judeh ◽  
Ming-Hsien Li
Keyword(s):  
Optimization Model ◽  
Real Life ◽  
Operating Rooms ◽  
Decision Makers ◽  
Operating Costs ◽  
Optimization Models ◽  
Patients Satisfaction ◽  
Fuzzy Scheduling ◽  
Sequencing Problems

AbstractLittle research has considered fuzzy scheduling and sequencing problem in operating rooms. Multiple-period fuzzy scheduling and sequencing of patients in operating rooms optimization models are proposed in this research taking into consideration patient‘s preference. The objective of the scheduling optimization model is obtaining minimal undertime and overtime and maximum patients' satisfaction about the assigned date. The objective of sequencing the optimization model is both to minimize overtime and to maximize patients' satisfaction about the assigned time. A real-life case study from a hospital that offers comprehensive surgical procedures for all surgical specialties is considered for illustration. Research results showed that the proposed models efficiently scheduled and sequenced patients while considering their preferences and hospitals operating costs. In conclusion, the proposed optimization models may result in improving patient satisfaction, utilizing hospital's resources efficiently, and providing assistance to decision makers and planners in solving effectively fuzzy scheduling and sequencing problems of operating rooms.

scholarly journals The Prejudicial Effects of "Reasonable Steps" in Analysis of Mens Rea and Sexual Consent: Two Solutions

2018 ◽  
pp. 933
Author(s):  
Lucinda Vandervort
Keyword(s):  
Sexual Assault ◽  
Personal Experience ◽  
Common Law ◽  
Criminal Code ◽  
Decision Makers ◽  
Sexual Consent ◽  
Mens Rea ◽  
State Of Mind ◽  
Definition Of ◽  
Is Failure

This article examines the operation of “reasonable steps” as a statutory standard for analysis of the availability of the defence of belief in consent in sexual assault cases and concludes that application of section 273.2(b) of the Criminal Code, as presently worded, often undermines the legal validity and correctness of decisions about whether the accused acted with mens rea, a guilty, blameworthy state of mind. When the conduct of an accused who is alleged to have made a mistake about whether a complainant communicated consent is assessed by the hybrid subjective-objective reasonableness standard prescribed by section 273.2, many decision-makers rely on extra-legal criteria and assumptions grounded in their personal experience and opinion about what is reasonable. In the midst of debate over what the accused knew and what steps were “reasonable,” given what the accused knew, the legal definition of consent in section 273.1 is easily overlooked and decision-makers focus on facts that are legally irrelevant and prejudice rational deliberation. The result is failure to enforce the law. The author proposes: (1) that section 273.2 be amended to reflect the significant developments achieved in sexual consent jurisprudence since enactment of the provision in 1992; and (2) that, in the interim, the judiciary act with resolve to make full and proper use of the statutory and common law tools that are presently available to determine whether the accused acted with mens rea in relation to the absence of sexual consent.

Conceptualizing Emergency Department Scenarios

2015 ◽  
pp. 1351-1368 ◽  
Author(s):  
Maya Kaner ◽  
Tamar Gadrich ◽  
Shuki Dror ◽  
Yariv N. Marmor
Keyword(s):  
Emergency Department ◽  
Real Life ◽  
Relevant Information ◽  
Literature Survey ◽  
Decision Makers ◽  
Simulation Experiments ◽  
Management Staff ◽  
Ed Operations ◽  
Relevant Factors

To handle problems and trends in emergency department (ED) operations, designers and decision makers often simulate and evaluate various case-specific scenarios before testing them in a real-life environment. However, conceptualizing broad possible scenarios for ED operations prior to simulation operationalization is usually neglected. The authors developed a methodology that integrates design of simulation experiments (DSE) as follows: 1) From a literature survey, they culled generic factors whose varying levels determine possible scenarios; 2) the authors drew up a set of generic interactions among these generic factors; 3) a questionnaire was constructed to serve as an instrument to gather the relevant information from management staff about relevant factors, their levels and interactions for a specific ED. Questionnaire responses support a schematic conceptualization of scenarios that should be simulated for a specific ED. They illustrate the application of the authors' methodology for conceptualization of ED simulation scenarios in two different EDs.

Frameworks and Models in Decision-Making and Judgment in Child Welfare and Protection

2020 ◽  
pp. 3-26
Author(s):  
Rami Benbenishty ◽  
John D. Fluke
Keyword(s):  
Decision Making ◽  
Information Processing ◽  
Child Welfare ◽  
False Negative ◽  
Real Life ◽  
Decision Makers ◽  
Future Research ◽  
Theoretical Perspectives ◽  
Specificity And Sensitivity ◽  
Predictive Risk

This chapter presents the basic concepts, theoretical perspectives, and areas of scholarship that bear on decisions in child welfare—making choices in decision environments characterized by high levels of uncertainty. The authors distinguish between normative models that predict what decision-makers ought to choose when faced with alternatives and descriptive models that describe how they tend to make these choices in real life. The chapter reviews those challenges that may be especially relevant in the complex context of child welfare and protection. One way in which decision-makers overcome task complexities and limitations in human information processing (bounded rationality) is by using heuristics to navigate complex tasks. The chapter reviews strategies to correct some limitations in judgment. The authors examine the relationships between workers’ predictions of what would be the outcomes of the case and the actual outcomes and describe two types of error (false positive and false negative) and the related concepts of specificity and sensitivity. These issues are followed by a description of the Lens Model and some of its implications for child welfare decision-making, including predictive risk modeling and studies on information processing models. The final section presents current theoretical models in child welfare decision-making and describes Decision-Making Ecology (DME) and Judgments and Decision Processes in Context (JUDPiC). The chapter concludes with suggestions for future research on child welfare decision-making that could contribute to our conceptual understanding and have practical utility as well.

An Application of the Integrated IBA-TOPSIS Model in Supplier Selection

2015 ◽  
Vol 7 (1) ◽  
pp. 15-30 ◽  
Author(s):  
Ksenija Mandić ◽  
Boris Delibašić ◽  
Dragan Radojević
Keyword(s):  
Decision Making ◽  
Boolean Algebra ◽  
Supplier Selection ◽  
Selection Process ◽  
Real Life ◽  
Decision Makers ◽  
Proposed Model ◽  
Qualitative Variables ◽  
Hidden Knowledge ◽  
Multi Attribute Decision Making

The supplier selection process attracted a lot of attention in the business management literature. This process takes into consideration several quantitative and qualitative variables and is usually modeled as a multi-attribute decision making (MADM) problem. A recognized shortcoming in the literature of classical MADM methods is that they don't permit the identification of interdependencies among attributes. Therefore, the aim of this study is to propose a model for selecting suppliers of telecommunications equipment that includes the interaction between attributes. This interaction can model the hidden knowledge needed for efficient decision-making. To model interdependencies among attributes the authors use a recently proposed consistent fuzzy logic, i.e. interpolative Boolean algebra (IBA). For alternatives ranking they use the classical MADM method TOPSIS. The proposed model was evaluated on a real-life application. The conclusion is that decision makers were able to integrate their reasoning into the MADM model using interpolative Boolean algebra.

Conceptualizing Emergency Department Scenarios

2013 ◽  
Vol 4 (1) ◽  
pp. 30-46
Author(s):  
Maya Kaner ◽  
Tamar Gadrich ◽  
Shuki Dror ◽  
Yariv Marmor
Keyword(s):  
Emergency Department ◽  
Real Life ◽  
Relevant Information ◽  
Literature Survey ◽  
Decision Makers ◽  
Simulation Experiments ◽  
Management Staff ◽  
Ed Operations ◽  
Relevant Factors

To handle problems and trends in emergency department (ED) operations, designers and decision makers often simulate and evaluate various case-specific scenarios before testing them in a real-life environment. However, conceptualizing broad possible scenarios for ED operations prior to simulation operationalization is usually neglected. The authors developed a methodology that integrates design of simulation experiments (DSE) as follows: 1) From a literature survey, they culled generic factors whose varying levels determine possible scenarios; 2) the authors drew up a set of generic interactions among these generic factors; 3) a questionnaire was constructed to serve as an instrument to gather the relevant information from management staff about relevant factors, their levels and interactions for a specific ED. Questionnaire responses support a schematic conceptualization of scenarios that should be simulated for a specific ED. They illustrate the application of the authors’ methodology for conceptualization of ED simulation scenarios in two different EDs.

scholarly journals A Game Theoretic Model of Choosing a Valuable Good via a Short List Heuristic

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 199 ◽  
Author(s):  
David M. Ramsey
Keyword(s):  
Real Life ◽  
Decision Makers ◽  
The Internet ◽  
Theoretic Model ◽  
Final Decision ◽  
Search Procedure ◽  
Short List ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
High Level

The Internet gives access to a huge amount of data at the click of a mouse. This is very helpful when consumers are making decisions about which product to buy. However, the final decision to purchase is still generally made by humans who have limited memory and perception. The short list heuristic is often used when there are many offers on the market. Searchers first find information about offers via the Internet and on this basis choose a relatively small number of offers to view in real life. Although such rules are often used in practice, little research has been carried out on determining, for example, what the size of the short list should be depending on the parameters of the problem or modelling how the short list heuristic can be implemented when there are multiple decision makers. This article presents a game theoretic model of such a search procedure with two players. These two players can be interpreted, for example, as a couple searching for a flat or a second-hand car. The model indicates that under such a search procedure the roles of searchers should only be divided when the preferences of the players are coherent or there is a high level of goodwill between them. In other cases, dividing the roles leads to a high level of conflict.

Coloured stochastic Petri nets modelling for the reliability and maintenance analysis of multi-state multi-unit systems

2014 ◽  
Vol 25 (4) ◽  
pp. 476-490 ◽  
Author(s):  
Zhouhang Wang ◽  
Maen Atli ◽  
H. Kondo Adjallah
Keyword(s):  
Petri Nets ◽  
Complex Structure ◽  
Real Life ◽  
Simulation Models ◽  
Decision Makers ◽  
Stochastic Petri Nets ◽  
Repairable Systems ◽  
Content Type ◽  
Markov Graphs ◽  
Maintenance Policies

Purpose – The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs. Design/methodology/approach – The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size. Findings – Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system. Research limitations/implications – The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered. Practical implications – The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies. Originality/value – The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

scholarly journals AHP-Group Decision Making Based on Consistency

Mathematics ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 242 ◽  
Author(s):  
Juan Aguarón ◽  
María Teresa Escobar ◽  
José Moreno-Jiménez ◽  
Alberto Turón
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Real Life ◽  
Decision Makers ◽  
Local Context ◽  
Consensus Matrix ◽  
Stability Intervals ◽  
The Individual ◽  
Individual Consistency

The Precise consistency consensus matrix (PCCM) is a consensus matrix for AHP-group decision making in which the value of each entry belongs, simultaneously, to all the individual consistency stability intervals. This new consensus matrix has shown significantly better behaviour with regards to consistency than other group consensus matrices, but it is slightly worse in terms of compatibility, understood as the discrepancy between the individual positions and the collective position that synthesises them. This paper includes an iterative algorithm for improving the compatibility of the PCCM. The sequence followed to modify the judgments of the PCCM is given by the entries that most contribute to the overall compatibility of the group. The procedure is illustrated by means of its application to a real-life situation (a local context) with three decision makers and four alternatives. The paper also offers, for the first time in the scientific literature, a detailed explanation of the process followed to solve the optimisation problem proposed for the consideration of different weights for the decision makers in the calculation of the PCCM.

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