An Optimization Approach to Balancing Risk and Cost in Combatant Command Capability Advocacy

Unified Combatant Commands (UCCs) have broad continuing missions around the globe where they are tasked to provide functional expertise and defense of geographical areas.  Accomplishing these missions requires a robust portfolio of military capabilities (e.g., aircraft, spacecraft, command and control systems, radar systems).  UCCs routinely perform analyses to identify gaps between capabilities required to accomplish their mission and those currently at their disposal.  Each year they submit a prioritized list of required capabilities, including new systems and greater capacity with existing systems, to the Joint Staff in the costly and time-consuming Integrated Priority List (IPL) process.  This process relies on operational art and subject matter expertise, and sometimes fails to identify acquisition opportunities that achieve an optimal balance between risk and cost.  Because this IPL process affects all of the DOD’s personnel, material, systems and missions, it is arguably the most significant analytic challenge faced by the United States military.  This article presents an integer linear programming model that computes an optimal balance between operational risk and the cost of acquiring new capabilities, and allows decision makers to identify the real-world impact of their budgetary decisions.  We apply this model to the mission of providing aerospace defense of the United States and illustrate through sensitivity analysis the meaningful insights that can be gained by studying the relationship between the risk of not achieving 100 percent radar coverage and the opportunity cost of advocating for new capabilities

Selection factor to bid or not to bid for extra low voltage system (ELV) project

Improper selection of Extra Low Voltage (ELV) projects by contractors might lead to many problems including underestimating cost of the project, lack of experience and bad quality of work. ELV system requires in-depth knowledge of technologies and a strong team of domain experts, who design, integrate and deliver Integrated ELV Systems that meet diverse needs. Therefore, the objectives of this study are to determine the factors of selecting an ELV Project by contractors, determine problems associated with current practice of project selection and to establish solutions that could improve future ELV projects selection. The methodology of this study will be divided into two stages which is primary data and secondary data. Secondary data will be collected by literature review by focusing on writing related materials and primary data will be collected by distributing a number of questionnaires that will determine later to selected respondents within company undertaking ELV projects. The collected data will then be analyzed using frequency distribution and average index method. The results of the study show resource pricing continuity of work/possible future project and return of investment is the most critical factors; meanwhile cost overrun, losing tender and defective works are among common problems that occurs with the current selection process; and submit the bid early, understand the client well and to sell on value are among the solutions with regard to ELV project selection criteria. The improvement will enhance business strategy for ELV contractors in project selection and future planning

A Pairwise Comparison Matrix Framework for Large-Scale Decision Making

abstract: A Pairwise Comparison Matrix (PCM) is used to compute for relative priorities of criteria or alternatives and are integral components of widely applied decision making tools: the Analytic Hierarchy Process (AHP) and its generalized form, the Analytic Network Process (ANP). However, a PCM suffers from several issues limiting its application to large-scale decision problems, specifically: (1) to the curse of dimensionality, that is, a large number of pairwise comparisons need to be elicited from a decision maker (DM), (2) inconsistent and (3) imprecise preferences maybe obtained due to the limited cognitive power of DMs. This dissertation proposes a PCM Framework for Large-Scale Decisions to address these limitations in three phases as follows. The first phase proposes a binary integer program (BIP) to intelligently decompose a PCM into several mutually exclusive subsets using interdependence scores. As a result, the number of pairwise comparisons is reduced and the consistency of the PCM is improved. Since the subsets are disjoint, the most independent pivot element is identified to connect all subsets. This is done to derive the global weights of the elements from the original PCM. The proposed BIP is applied to both AHP and ANP methodologies. However, it is noted that the optimal number of subsets is provided subjectively by the DM and hence is subject to biases and judgement errors. The second phase proposes a trade-off PCM decomposition methodology to decompose a PCM into a number of optimally identified subsets. A BIP is proposed to balance the: (1) time savings by reducing pairwise comparisons, the level of PCM inconsistency, and (2) the accuracy of the weights. The proposed methodology is applied to the AHP to demonstrate its advantages and is compared to established methodologies. In the third phase, a beta distribution is proposed to generalize a wide variety of imprecise pairwise comparison distributions via a method of moments methodology. A Non-Linear Programming model is then developed that calculates PCM element weights which maximizes the preferences of the DM as well as minimizes the inconsistency simultaneously. Comparison experiments are conducted using datasets collected from literature to validate the proposed methodology.Dissertation/ThesisPh.D. Industrial Engineering 201

FIST and the Analytical Hierarchy Process: Comparative Modeling

FIST is an emerging and unproven rapid acquisition model that stands for Fast, Inexpensive, Simple, and Tiny. The purpose of this research is to develop an Analytical Hierarchy Process (AHP) model based on the FIST concepts, to be applied as a comparative tool against the FIST model. The results indicate that the FIST model is reproducible with the AHP theory and that there are certain program characteristics that denote if a program would benefit from being developed by FIST. However, there are distinct weaknesses to the model that signify not all programs would succeed if FIST was employed during development. Eleven additional FIST activities are recommended for inclusion in the model with key activities comprising of an ambidextrous structured organization, better requirements gathering techniques, and utilizing incremental development

Approaches to selecting information systems projects under uncertainty

The rapid advance in information and communication technologies has effectively facilitated the development and implementation of information systems (IS) projects in modern organizations for reorganizing their business processes and streamlining the provision of their products and services in today's dynamic environment. Such a development brings organizations with numerous benefits including increased automation of business processes, improved customer service, and timely provision of effective decision support. As a result, evaluating and selecting the most appropriate IS project for development and implementation from a pool of available IS projects becomes a critical decision to make in modern organizations. Evaluating and selecting appropriate IS projects for development in an organization, however, is complex and challenging. The complexity of the evaluation and selection process is due to the multi-dimensional nature of the decision making process, the conflicting nature of the multiple selection criteria, and the presence of subjectiveness and imprecision of the human decision making process. The challenging of the evaluation and selection comes from the need for making transparent and balanced decisions based on a comprehensive evaluation of all available IS projects in a timely manner. Much research has been done on the development of various approaches for evaluating and selecting IS projects, and numerous applications of those approaches for addressing real world IS project evaluation and selection problems have been reported in the literature. In general, existing approaches can be classified into (a) cost-benefit analysis based approaches, (b) utility based approaches, and (c) optimization oriented approaches. These approaches, however, are not totally satisfactory due to various shortcomings including (a) the inability to tackle the subjectiveness and imprecision of the selection process, (b) the failure to adequately handle the multi-dimensional nature of the problem, and (c) cognitively very demanding on the decision maker. To address these issues above, this research has developed three novel approaches for effectively solving the IS project evaluation and selection problem under uncertainty in an organization. The first approach is developed for helping the decision maker better model the subjectiveness and imprecision inherent in the decision-making process with the use of linguistic variables approximated by fuzzy numbers. The second approach is designed to reduce the cognitive demanding on the decision maker in the IS project evaluation and selection process with the introduction of fuzzy pairwise comparison. The third approach is formulated with respect to the use of intelligent decision support systems for facilitating the use of specific multi-criteria analysis approaches in relation to individual IS project evaluation and selection situations. The developed approaches have been applied for solving three IS project evaluation and selection problems in the real world settings. The results show that the three developed ap proaches are of practical significance for effectively and efficiently solving the IS project evaluation and selection problem due to (a) the simplicity and comprehensibility of the underlying concept, (b) the adequate handling of inherent uncertainty and imprecision, and (c) the ability to help the decision maker better understand the IS project selection problem and the implications of their decision behaviours

Air Force Institute of Technology Research Report 2003

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

Some further studies on improving QFD methodology and analysis

Quality Function Deployment (QFD) starts and ends with the customer. In other words, how it ends may depend largely on how it starts. Any QFD practitioners will start with collecting the voice of the customer that reflects customer’s needs as to make sure that the products will eventually sell or the service may satisfy the customer. On the basis of those needs, a product or service creation process is initiated. It always takes a certain period of time for the product or service to be ready for the customer. The question here is whether those customer-needs may remain exactly the same during the product or service creation process. The answer would be very likely to be a ‘no’, especially in today’s rapidly changing environment due to increased competition and globalization. The focus of this thesis is placed on dealing with the change of relative importance of the customer’s needs during product or service creation process. In other words, the assumption is that there is no new need discovered along the time or an old one becomes outdated; only the relative importance change of the existing needs is dealt with. Considering the latest development of QFD research, especially the increasingly extensive use of Analytic Hierarchy Process (AHP) in QFD, this thesis aims to enhance the current QFD methodology and analysis, with respect to the change during product or service creation process, as to continually meet or exceed the needs of the customer. The entire research works are divided into three main parts, namely, the further use of AHP in QFD, the incorporation of AHP-based priorities’ dynamics in QFD, and decision making analysis with respect to the dynamics. The first part focuses on the question "In what ways does AHP, considering its strength and weakness, contribute to an improved QFD analysis?" The usefulness of AHP in QFD is demonstrated through a case study in improving higher education quality of an education institution. Furthermore, a generalized model of using AHP in QFD is also proposed. The generalized model not only provides an alternative way to construct the house of quality (HoQ), but also creates the possibility to include other relevant factors into QFD analysis, such as new product development risks. The second part addresses the question "How to use the AHP in QFD in dealing with the dynamics of priorities?" A novel quantitative method to model the dynamics of AHP-based priorities in the HoQ is proposed. The method is simple and time-efficient. It is especially useful when the historical data is limited, which is the case in a highly dynamic environment. As to further improve QFD analysis, the modeling method is applied into two areas. The first area is to enhance the use of Kano’s model in QFD by considering its dynamics. It not only extends the use of Kano’s model in QFD, but also advances the academic literature on modeling the life cycle of quality attributes quantitatively. The second area is to enhance the benchmarking part of QFD by including the dynamics of competitors’ performance in addition to the dynamics of customer’s needs. The third part deals with the question "How to make decision in a QFD analysis with respect to the dynamics in the house of quality?" Two decision making approaches are proposed to prioritize and/or optimize the technical attributes with respect to the modeling results. Considering the fact that almost all QFD translation process employs the relationship matrix, a guideline for QFD practitioners to decide whether the relationship matrix should be normalized is developed. Furthermore, a practical implication of the research work towards the possible use of QFD in helping a company develop more innovative products is also discussed. In brief, the main contribution of this thesis is in providing some novel methods and/or approaches to enhance the QFD’s use with respect to the change during product or service creation process. For scientific community, this means that the existing QFD research has been considerably improved, especially with the use of AHP in QFD. For engineering practice, a better way of doing QFD analysis, as a customer-driven engineering design tool, has been proposed. It is hoped that the research work may provide a first step into a better customer-driven product or service design process, and eventually increase the possibility to create more innovative and competitive products or services over time

Some further studies on improving QFD methodology and analysis

Ph.DNUS-TU/E JOINT PH.D. PROGRAMM