scholarly journals Supporting Operations Management Decisions with LP Parametric Analyses Using AIMMS

2020 ◽  
Vol 28 (2) ◽  
pp. 91-100
Author(s):  
Imre Dimény ◽  
Tamás Koltai
Keyword(s):  
Decision Making ◽  
Operations Management ◽  
Business Strategy ◽  
Optimal Solution ◽  
Computation Time ◽  
Valuable Insight ◽  
Business Analytics ◽  
Hard Time ◽  
Wide Range ◽  
Parametric Analyses

Organizations all over the world use Business Analytics (BA) to gain insight in order to drive business strategy and planning. With the increasing amount of available data larger models are created to support decision making, but managers also must deal with the uncertainty of the input parameters. In this perspective Linear Programming (LP) models have two valuable properties: the required computation time allows large models to be solved and further valuable insight can be gained about the problem using sensitivity analysis. There is a wide range of tools available to solve LP problems. Many of these tools use an implementation of the simplex method and provides an optimal solution related sensitivity information. The sensitivity information generated by such solvers are often used by managers in the decision making process. There are situations when managers may have a hard time taking decision based on the information provided by most of the commercially available LP solvers. If the optimal solution of the primal problem (dual degeneracy) or the dual problem (primal degeneracy) is not unique, the resulting sensitivity information can be misleading for managers. In other cases, the resulted ranges may be too tight for decision support, thus information about a wider range is required. In this paper parametric analysis information is recommended to complete the traditional LP results in order to increase the insight of operations managers when using LP models for operation improvement.

scholarly journals Constructing Taipei City Sports Centre Performance Evaluation Model with Fuzzy MCDM Approach Based on Views of Managers

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Chen-Yang Wang ◽  
Pei-Hsuan Tsai ◽  
Hu Zheng
Keyword(s):  
Decision Making ◽  
Operations Management ◽  
Business Strategy ◽  
Evaluation Model ◽  
Management Strategies ◽  
Business Management ◽  
Practical Experience ◽  
Priority Service ◽  
Network Process ◽  
Six Dimensions

This study aims to utilize the fuzzy analytical/network process (FAHP/FANP) and decision-making trial and evaluation laboratory (DEMATEL) approach to recognize the influential indicators of sport centre business management in Taipei city’s sports centre. Twenty-three of sports centres with six-dimensions were identified from the literature review and interview with twelve experts (academic and practical experience). By considering the interrelationships among the indices, DEMATEL was used to deal with the importance and causal relationships among the evaluation indices of sports centre. Then, we employ the FAHP/FANP to determine the weight of each management criterion. Our empirical results provide two main insights: first, sports centre business management strategies comprise six-dimensions and 23 indexes; second, the FANP analysis shows that the six key factors are (in order of priority) service price, site conditions, operations management, traffic conditions, sports products, and staff quality. This study uses the FANP and DEMATEL along with mathematical computing in order to provide sports centre managers with a reliable decision-making reference and to assist them in formulating the most effective business strategy possible.

scholarly journals Grouping and analysis of chair quality and their basic elements

2009 ◽  
pp. 147-154 ◽  
Author(s):  
Dusan Skakic ◽  
Igor Dzincic
Keyword(s):  
Finite Element Method ◽  
Decision Making ◽  
Finite Element ◽  
Numerical Optimization ◽  
Optimal Solution ◽  
Engineering Practice ◽  
The Finite Element Method ◽  
Wide Range ◽  
Decision Making Processes ◽  
Selection Of

Both the scientific experience and the engineering practice indicate that the decision making processes in the course of solving complex designing problems require an analysis of a great number of different construction variants. These types of decision-making processes are time consuming and do not always result in the selection of an optimal solution. That is why the methods of numerical optimization are applied in a wide range of technical sciences to assist in the selection of the best solution. The first step in solving the problem by using the Finite element method is to determine the type of chair earmarked for modeling, and to determine the dimensions of the chair elements.

Searching for Herbert Simon

2013 ◽  
Vol 4 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Michael F. Gorman ◽  
Donald E. Wynn ◽  
William David Salisbury
Keyword(s):  
Decision Making ◽  
Analytical Techniques ◽  
Decision Makers ◽  
Business Analytics ◽  
Herbert Simon ◽  
Business Decision ◽  
Wide Range ◽  
Human Decision ◽  
Potential Impact ◽  
Effective Use

Since Herbert Simon’s seminal work (Simon, 1957) on bounded rationality researchers and practitioners have sought the “holy grail” of computer-supported decision-making. A recent wave of interest in “business analytics” (BA) has elevated interest in data-driven analytical decision making to the forefront. While reporting and prediction via business intelligence (BI) systems has been an important component to business decision making for some time, BA broadens its scope and potential impact in business decision making further by moving the focus to prescription. The authors see BA as the end-to-end process integrating the production through consumption of the data, and making more extensive use of the data through heavily automated, integrated and advanced predictive and prescriptive tools in ways that better support, or replace, the human decision maker. With the advent of “big data”, BA already extends beyond internal databases to external and unstructured data that is publicly produced and consumed data with new analytical techniques to better enable business decision makers in a connected world. BI research in the future will be broader in scope, and the challenge is to make effective use of a wide range of data with varying degrees of structure, and from sources both internal and external to the organization. In this paper, we suggest ways that this broader focus of BA will also affect future BI research streams.

EBDMSS

2012 ◽  
pp. 265-284
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.

scholarly journals A Knowledge Management Challenges for Start-Ups: A Framework Proposal

2020 ◽  
Vol 3 (3) ◽  
pp. 248-260
Author(s):  
Theocharis Stylianos Spyropoulos
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Business Strategy ◽  
Success Factors ◽  
Innovation Management ◽  
Technical Information ◽  
Business Environment ◽  
Online Information ◽  
Wide Range ◽  
Start Ups

The study reviews the knowledge management challenges faced by innovative start-ups founders and entrepreneurs. Knowledge management is critical for innovation, since both organisations and individuals face very specific needs: collection of a wide variety of information and data, such as market data and technical information, and a wide range of transformation of these data into applicable knowledge, in the forms of required product specifications, business model, and business strategy. In addition, the business financing and investment ecosystem (especially Banks & Venture Capitals) uses a traditional “business plan” approach for evaluating innovation companies. Furthermore, a wide range of tools (databases, online information, Collaboration Systems, Business Intelligence Systems, ERP & CRM Systems) enable information flow and supports decision making process. To this respect, both academic literature and business experience highlight the need to improve Knowledge Management process both for individuals and organisations engaged in Innovation management. The proposed framework provides academics, entrepreneurs and venture capital companies a new approach for identifying critical success factors knowledge management and further improves decision making in a changing and challenging business environment. Finally the study highlights key areas for further research.

EBDMSS

2011 ◽  
pp. 549-568
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.

EBDMSS

2010 ◽  
Vol 2 (4) ◽  
pp. 50-68 ◽  
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Management ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.

scholarly journals A Bilinear Programming Approach for Multiagent Planning

2009 ◽  
Vol 35 ◽  
pp. 235-274 ◽  
Author(s):  
M. Petrik ◽  
S. Zilberstein
Keyword(s):  
Reduction Method ◽  
Optimal Solution ◽  
Computation Time ◽  
Bilinear Programming ◽  
Programming Approach ◽  
Performance Bound ◽  
Wide Range ◽  
Multiagent Planning ◽  
Dimensionality Reduction Method ◽  
Bilinear Programs

Multiagent planning and coordination problems are common and known to be computationally hard. We show that a wide range of two-agent problems can be formulated as bilinear programs. We present a successive approximation algorithm that significantly outperforms the coverage set algorithm, which is the state-of-the-art method for this class of multiagent problems. Because the algorithm is formulated for bilinear programs, it is more general and simpler to implement. The new algorithm can be terminated at any time and-unlike the coverage set algorithm-it facilitates the derivation of a useful online performance bound. It is also much more efficient, on average reducing the computation time of the optimal solution by about four orders of magnitude. Finally, we introduce an automatic dimensionality reduction method that improves the effectiveness of the algorithm, extending its applicability to new domains and providing a new way to analyze a subclass of bilinear programs.

scholarly journals A survey of methods for evaluating mini-publics

2021 ◽  
Author(s):  
Takeuchi Ayano
Keyword(s):  
Decision Making ◽  
Academic Research ◽  
Future Research ◽  
The Political ◽  
Decision Making Process ◽  
Sufficient Information ◽  
Practical Case ◽  
Political Decision ◽  
Wide Range ◽  
Political Decision Making

AbstractPublic participation has become increasingly necessary to connect a wide range of knowledge and various values to agenda setting, decision-making and policymaking. In this context, deliberative democratic concepts, especially “mini-publics,” are gaining attention. Generally, mini-publics are conducted with randomly selected lay citizens who provide sufficient information to deliberate on issues and form final recommendations. Evaluations are conducted by practitioner researchers and independent researchers, but the results are not standardized. In this study, a systematic review of existing research regarding practices and outcomes of mini-publics was conducted. To analyze 29 papers, the evaluation methodologies were divided into 4 categories of a matrix between the evaluator and evaluated data. The evaluated cases mainly focused on the following two points: (1) how to maintain deliberation quality, and (2) the feasibility of mini-publics. To create a new path to the political decision-making process through mini-publics, it must be demonstrated that mini-publics can contribute to the decision-making process and good-quality deliberations are of concern to policy-makers and experts. Mini-publics are feasible if they can contribute to the political decision-making process and practitioners can evaluate and understand the advantages of mini-publics for each case. For future research, it is important to combine practical case studies and academic research, because few studies have been evaluated by independent researchers.

scholarly journals Results of the Behavioral Health Readiness Evaluation and Decision-Making Instrument Study

2021 ◽  
Vol 186 (Supplement_1) ◽  
pp. 142-152
Author(s):  
Justin M Curley ◽  
Katie L Nugent ◽  
Kristina M Clarke-Walper ◽  
Elizabeth A Penix ◽  
James B Macdonald ◽  
...  
Keyword(s):  
Decision Making ◽  
Behavioral Health ◽  
User Satisfaction ◽  
Safety Issue ◽  
Walter Reed Army Institute ◽  
End User ◽  
Chi Square ◽  
Proficiency Level ◽  
Wide Range ◽  
Decision Making Support

ABSTRACT Introduction Recent reports have demonstrated behavioral health (BH) system and individual provider challenges to BH readiness success. These pose a risk to winning on the battlefield and present a significant safety issue for the Army. One of the most promising areas for achieving better BH readiness results lies in improving readiness decision-making support for BH providers. The Walter Reed Army Institute of Research (WRAIR) has taken the lead in addressing this challenge by developing and empirically testing such tools. The results of the Behavioral Health Readiness Evaluation and Decision-Making Instrument (B-REDI) field study are herein described. Methods The B-REDI study received WRAIR Institutional Review Board approval, and BH providers across five U.S. Army Forces Command installations completed surveys from September 2018 to March 2019. The B-REDI tools/training were disseminated to 307 providers through random clinic assignments. Of these, 250 (81%) providers consented to participate and 149 (60%) completed both initial and 3-month follow-up surveys. Survey items included a wide range of satisfaction, utilization, and proficiency-level outcome measures. Analyses included examinations of descriptive statistics, McNemar’s tests pre-/post-B-REDI exposure, Z-tests with subgroup populations, and chi-square tests with demographic comparisons. Results The B-REDI resulted in broad, statistically significant improvements across the measured range of provider proficiency-level outcomes. Net gains in each domain ranged from 16.5% to 22.9% for knowledge/awareness (P = .000), from 11.1% to 15.8% for personal confidence (P = .001-.000), and from 6.2% to 15.1% for decision-making/documentation (P = .035-.002) 3 months following B-REDI initiation, and only one (knowledge) failed to maintain a statistically significant improvement in all of its subcategories. The B-REDI also received high favorability ratings (79%-97% positive) across a wide array of end-user satisfaction measures. Conclusions The B-REDI directly addresses several critical Army BH readiness challenges by providing tangible decision-making support solutions for BH providers. Providers reported high degrees of end-user B-REDI satisfaction and significant improvements in all measured provider proficiency-level domains. By effectively addressing the readiness decision-making challenges Army BH providers encounter, B-REDI provides the Army BH health care system with a successful blueprint to set the conditions necessary for providers to make more accurate and timely readiness determinations. This may ultimately reduce safety and mission failure risks enterprise-wide, and policymakers should consider formalizing and integrating the B-REDI model into current Army BH practice.

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