Sustainability concerns are increasingly shaping customers' behavior as well as companies' strategy. In this context, optimizing the supply chain with sustainability considerations is becoming a critical issue. However, work with quantitative models is still scarce. Our research contributes by revisiting classical inventory models taking sustainability concerns into account. We believe that reducing all aspects of sustainable development to a single objective is not desirable. We thus reformulate single and multi-echelon economic order quantity models as multi-objective problems. These models are then used to study several options such as buyer-supplier coordination or green technology investment. We also consider that firms are becoming increasingly proactive with respect to sustainability. We thus propose to apply multiple criteria decision aid techniques instead of considering sustainability as a constraint. In this sense, the firm may provide preference information about economic, environmental and social tradeoffs and quickly identify a satisfactory solution.

Flexible approaches for eliciting preferences of decision makers involved in a conflict are developed along with applications to real-world disputes. More specifically, two multiple criteria decision making approaches are proposed for capturing the relative preferences of a decision maker participating in a conflict situation. A case study in logistics concerned with the conflict arising over the expansion of port facilities on the west coast of North America as well as a transportation negotiation dispute are used to illustrate how these approaches can be integrated with the Graph Model for Conflict Resolution, a practical conflict analysis methodology. Ascertaining the preferences of the decision makers taking part in a conflict constitutes a key element in the construction of a formal conflict model. In practice, the relative preferences, which reflect each decision maker’s objectives or goals in a given situation, are rather difficult to obtain. The first method for preference elicitation is to integrate an Analytic Hierarchy Process (AHP) preference ranking method with the Graph Model for Conflict Resolution. The AHP approach is used to elicit relative preferences of decision makers, and this preference information is then fed into a graph model for further stability analyses. The case study of the Canadian west coast port congestion conflict is investigated using this integrated model. Another approach is based on a fuzzy multiple criteria out-ranking technique called ELECTRE III. It is also employed for ranking states or possible scenarios in a conflict from most to least preferred, with ties allowed, by the decision maker according to his or her own value system. The model is applied to a transportation negotiation dispute between the two key parties consisting of shippers and carriers.

Flexible approaches for eliciting preferences of decision makers involved in a conflict are developed along with applications to real-world disputes. More specifically, two multiple criteria decision making approaches are proposed for capturing the relative preferences of a decision maker participating in a conflict situation. A case study in logistics concerned with the conflict arising over the expansion of port facilities on the west coast of North America as well as a transportation negotiation dispute are used to illustrate how these approaches can be integrated with the Graph Model for Conflict Resolution, a practical conflict analysis methodology. Ascertaining the preferences of the decision makers taking part in a conflict constitutes a key element in the construction of a formal conflict model. In practice, the relative preferences, which reflect each decision maker’s objectives or goals in a given situation, are rather difficult to obtain. The first method for preference elicitation is to integrate an Analytic Hierarchy Process (AHP) preference ranking method with the Graph Model for Conflict Resolution. The AHP approach is used to elicit relative preferences of decision makers, and this preference information is then fed into a graph model for further stability analyses. The case study of the Canadian west coast port congestion conflict is investigated using this integrated model. Another approach is based on a fuzzy multiple criteria out-ranking technique called ELECTRE III. It is also employed for ranking states or possible scenarios in a conflict from most to least preferred, with ties allowed, by the decision maker according to his or her own value system. The model is applied to a transportation negotiation dispute between the two key parties consisting of shippers and carriers.

In this thesis, we develop two exact algorithms and a heuristic procedure for Multiobjective Combinatorial Optimization Problems (MOCO). Our exact algorithms guarantee to generate all nondominated solutions of any MOCO problem. We test the performance of the algorithms on randomly generated problems including the Multiobjective Knapsack Problem, Multi-objective Shortest Path Problem and Multi-objective Spanning Tree Problem. Although we showed the algorithms work much better than the previous ones, we also proposed a fast heuristic method to approximate efficient frontier since it will also be applicable for real-sized problems. Our heuristic approach is based on fitting a surface to approximate the efficient frontier. We experiment our heuristic on randomly generated problems to test how well the heuristic procedure approximates the efficient frontier. Our results showed the heuristic method works well.

This study addresses sorting problems with predefined ordinal classes. We develop a new method based on Support Vector Machine (SVM) model, which is mainly used for nominal binary or multi-class classification processes. In the proposed method, the SVM model is extended to include the preferences of the decision maker and the ordinal relationship between classes in sorting problems. New sets of constraints are added to the SVM model. We demonstrate the performance of the proposed method through several data sets. We compare the results with those of classical SVM model and UTADIS method, a well-known multiple criteria sorting method. We also analyze the effect of feature space mapping by Kernel Trick utilization on the results.

The use of architectures for the design, development, and documentation of system-of-systems engineering has become a common practice in recent years. At the same time, acquisition guidance has been recently reformed to move from the bottom-up approach of the Requirements Generation System (RGS) to the top-down approach mandated by the Joint Capabilities Integration and Development System (JCIDS), which requires the use of DoDAF to support acquisition. Defense agencies have had difficulty adjusting to these new policies, and are struggling to determine how to meet new acquisition requirements. This research has developed the Architecture-based Technology Evaluation and Capability Tradeoff (ARCHITECT) Methodology to respond to these challenges and address concerns raised about the defense acquisition process. The methodology integrates existing tools and techniques for systems engineering and system of systems engineering with several new modeling and simulation tools and techniques developed as part of this research to fill gaps noted in prior CBAs. Additional criteria for the methodology were developed by leveraging lessons learned from similar fields, including management science and cognitive psychology. A suppression of enemy air defenses (SEAD) mission is used to demonstrate the application of ARCHITECT and to show the plausibility of the approach. Overall, it is shown that the ARCHITECT methodology results in an improvement over current CBAs in the criteria developed here.

An Architecture Real Options Complexity-Based Valuation Methodology (ARC-VM) is developed for use to aid in the acquisition of military systems-of-systems (SoS). ARC-VM is suitable for acquisition-level decision making, where there is a stated desire for more informed tradeoffs between cost, schedule, and performance during the early phases of design. First, a framework is introduced to measure architecture complexity as it directly relates to military SoS. Development of the framework draws upon a diverse set of disciplines, including Complexity Science, software architecting, measurement theory, and utility theory. Next, a Real Options based valuation strategy is developed using techniques established for financial stock options that have recently been adapted for use in business and engineering decisions. The derived complexity measure provides architects with an objective measure of complexity that focuses on relevant complex system attributes. These attributes are related to the organization and distribution of SoS functionality and the sharing and processing of resources. The use of Real Options provides the necessary conceptual and visual framework to quantifiably and traceably combine measured architecture complexity, time-valued performance levels, as well as programmatic risks and uncertainties. An example suppression of enemy air defenses (SEAD) capability demonstrates the development and utility of the resulting architecture complexity&Real Options based valuation methodology. Different portfolios of candidate system types are used to generate an array of architecture alternatives that are then evaluated using an engagement model. This performance data is combined with both measured architecture complexity and programmatic data to assign an acquisition value to each alternative. This proves useful when selecting alternatives most likely to meet current and future capability needs.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 164-175). Also available on the Internet.

Thesis supervisor: Michael S. Lewis-Beck. Thesis supervisor: David Redlawsk. Includes bibliographic references (p. 187-195).

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references (leaves 164-175). Also available on the Internet.