Multi-criteria scheduling provides the opportunity to create mathematical optimization models that are applicable to a diverse set of problem domains in the business world. This research addresses two different employee scheduling applications using multi-criteria objectives that present decision makers with trade-offs between global optimality and the level of disruption to current operating resources. Additionally, it investigates a scheduling problem from the product testing domain and proposes a heuristic solution technique for the problem that is shown to produce very high-quality solutions in short amounts of time. Chapter 2 addresses a grant administration workload-to-staff assignment problem that occurs in the Office of Research and Sponsored Programs at land-grant universities. We identify the optimal workload assignment plan which differs considerably due to multiple reassignments from the current state. To achieve the optimal workload reassignment plan we demonstrate a technique to identify the n best reassignments from the current state that provides the greatest progress toward the utopian solution. Solving this problem over several values of n and plotting the results allows the decision maker to visualize the reassignments and the progress achieved toward the utopian balanced workload solution. Chapter 3 identifies a weekly schedule that seeks the most cost-effective set of coach-to-program assignments in a gymnastics facility. We identify the optimal assignment plan using an integer linear programming model. The optimal assignment plan differs greatly from the status quo; therefore, we utilize a similar approach from Chapter 2 and use a multiple objective optimization technique to identify the n best staff reassignments. Again, the decision maker can visualize the trade-off between the number of reassignments and the resulting progress toward the utopian staffing cost solution and make an informed decision about the best number of reassignments. Chapter 4 focuses on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Each product receives a certification at the successful completion of a predetermined series of tests. Operational efficiency is enhanced by determining the optimal order and start times of tests so as to minimize the make span while ensuring that technicians are available when needed to complete in-process and at-completion inspections We first formulate a mixed-integer programming model (MILP) to identify the optimal solution to this problem using IBM ILOG CPLEX Interactive Optimizer 12.7. We also present a genetic algorithm (GA) solution that is implemented and solved in Microsoft Excel. Computational results are presented demonstrating the relative merits of the MILP and GA solution approaches across a number of scenarios. / Ph. D. / Multi-criteria scheduling provides the opportunity to create mathematical optimization models that are applicable to a diverse set of problem domains in the business world. This research addresses two different employee scheduling applications using multi-criteria objectives that present decision makers with trade-offs between global optimality and the level of disruption to current operating resources. Additionally, it investigates a scheduling problem from the product testing domain and proposes a heuristic solution technique for the problem that is shown to produce very high-quality solutions in short amounts of time. Chapter 2 addresses a grant administration workload-to-staff assignment problem that occurs in the Office of Research and Sponsored Programs at land-grant universities. Solving this problem and plotting the results allows the decision maker to visualize the number of reassignments and the progress achieved toward the utopian balanced workload solution. Chapter 3 identifies a weekly schedule that seeks the most cost-effective set of coach-to-program assignments in a gymnastics facility. Again, the decision maker can visualize the trade-off between the number of reassignments and the resulting progress toward the utopian staffing cost solution and make an informed decision about the best number of reassignments. Chapter 4 focuses on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Each product receives a certification at the successful completion of a predetermined series of tests. Computational results are presented demonstrating the relative merits of the mixed integer linear programming model and the genetic algorithm solution approaches across a number of scenarios.

The efficiency of a best management practice (BMP) is defined simply as a measure of how well the practice or series of practices removes targeted pollutants. While this concept is relatively simple, mathematical attempts to quantify BMP efficiency are numerous and complex. Intuitively, the pollutant removal capability of a BMP should be fundamental to the BMP selection process. However, as evidenced by the absence of removal efficiency as an influential criterion in many BMP selection procedures, it is typically not at the forefront of the BMP selection and design process. Additionally, of particular interest to any developer or municipal agency is the financial impact of implementing a BMP. Not only does the implementation cost exist, but there are long-term maintenance costs associated with almost any BMP. Much like pollutant removal efficiency, implementation and maintenance costs seem as though they should be integral considerations in the BMP selection process. However, selection flow charts and matrices employed by many localities neglect these considerations. Among the categories of criteria to consider in selecting a BMP for a particular site or objective are site-specific characteristics; local, state, and federal ordinances; and implementation and long-term maintenance costs. A consideration such as long-term maintenance cost may manifest itself in a very subjective fashion during the selection process. For example, a BMPs cost may be of very limited interest to the reviewing locality, whereas cost may be the dominant selection criterion in the eyes of a developer. By contrast, the pollutant removal efficiency of a BMP may be necessarily prioritized in the selection process because of the required adherence to governing legislation. These are merely two possible criteria influencing selection. As more and more selection criteria are considered, the task of objectively and optimally selecting a BMP becomes increasingly complex. One mathematical approach for optimization in the face of multiple influential criteria is the Analytic Hierarchy Process. "The analytic hierarchy process (AHP) provides the objective mathematics to process the inescapably subjective and personal preferences of an individual or a group in making a decision" (Schmoldt, 2001, pg. 15). This paper details the development of two categories of comprehensive BMP selection matrices expressing long-term pollutant removal performance and annual maintenance and operations cost respectively. Additionally, the AHP is applied in multiple scenarios to demonstrate the optimized selection of a single BMP among multiple competing BMP alternatives. Pairwise rankings of competing BMP alternatives are founded on a detailed literature review of the most popular BMPs presently implemented throughout the United States. / Master of Science

No / In recent decades, sustainable investing has caught on with investors, and it has now become the norm. In the age of start-ups, with scant information on the sustainability aspects of an asset, it becomes harder to pursue sustainable investing. To this end, this paper proposes a sustainable financial portfolio selection approach in an intuitionistic fuzzy framework. We present a comprehensive three-stage methodology in which the assets under consideration are ethically screened in Stage-I. Stage-II is concerned with cal- culating the sustainability scores, based on various social, environmental, and economic (SEE) criteria and an evaluation of the return and risk of the ethical assets. Intuitionistic fuzzy set theory is used to gauge the linguistic assessment of the assets on several SEE criteria from multiple decision-makers. A novel intuitionistic fuzzy multi-criteria group decision-making technique is applied to calculate the sustainability score of each asset. Finally, in Stage-III, an intuitionistic fuzzy multi-objective financial portfolio selection model is developed with maximization of the satisfaction degrees of the sustainabil- ity score, return, and risk of the portfolio, subject to several constraints. The ε-constraint method is used to solve this model, which yields various efficient, sustainable financial portfolios. Subsequently, investors can choose the portfolio best suited to their preferences from this pool of efficient, sustainable financial portfolios. A detailed empirical illustration and a comparison with existing works are given to substantiate and validate the proposed approach. / Institution of Eminence, University of Delhi, Delhi-110007 under Faculty Research Program

Yes / Performance evaluation has been an important topic of concern for tourism industry practitioners as well as academic researchers, and its investigation in the UK hotel sector is paramount because this industry has been experiencing a higher level of competition. The present study contributes to the previous literature on hotel performance evaluation in general by proposing an innovative hybrid method combining the second-order cone programming (SOCP) method and multi-criteria decision-making (MCDM) method to estimate the performance of the UK hotel sector. The innovation lies in the synergistic combination of SOCP and MCDM methodologies, enabling a comprehensive assessment of hotel performance by managing a non-linear optimisation. Overall, this hybrid method benefits from the ability to be more flexible in addressing complex operational issues and provide more accurate results. This research provides a cost-benefit analysis within the proposed method, suggesting important policy implications in the tourism industry. / The full-text of this article will be released for public view at the end of the publisher embargo on 30 Aug 2026.

Yes / Performance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehensive approach as a response to the major shortcomings of the generic BSC regarding the negligence of different stakeholders. Subsequently, since the indicators are not independent of each other, a robust multi-criteria decision making technique, the Analytic Network Process (ANP) method is implemented to analyze the interrelationships. The integration of these two techniques provides a novel way to evaluate logistics performance indicators from logisticians' perspective. This is a matter that has not been addressed in the logistics industry to date, and as such remains a gap that needs to be investigated. Therefore, the proposed model identifies key performance indicators as well as various stakeholders in the logistics industry, and analyzes the interrelationships among the indicators by using the ANP. Consequently, the results show that educated employee (15.61%) is the most important indicator for the competitiveness of logistics companies.

Yes / The surface transport infrastructure (i.e. road and rail) has seen increasing pressure in recent years to achieve better sustainability performance. Transport Noise Reducing Devices (NRDs) form a major part of the surface transport infrastructure system in mitigating undesirable surface noise pollution to impacted communities. Their sustainability is a growing interest for practitioners and policy makers in this area as NRDs projects now have to balance integrating and assessing social, environmental, and economic objectives besides meeting key technical requirements. This paper presents an account of the first study carried out to assess the absolute sustainability of NRDs via the application of multi criteria analysis (MCA) techniques. The general procedure, selection of criteria, data gathering, and the use of three MCA techniques, SAW (Simple Additive Weighting), PROMETHEE (Preference Ranking Organisation MeTHod for Enrichment Evaluations), and ELECTRE III (Elimination et Choice Translating Reality), to assess the absolute sustainability of two built and operating European NRDs projects (one in Spain, and one in Italy) is presented. The novel concept of defining an Optimal Hypothetic Ideal Solution (OHIS) to assess the sustainability of NRDs in absolute terms to achieve this end is also introduced and discussed. The presented case studies will thus provide a useful model for practitioners to adopt or amend to conduct their own assessments of NRDs' sustainability. The paper further concludes that the generation of index values by the three MCA techniques to denote the overall absolute sustainability of solutions is a useful feature for communicating the sustainability of NRDs across a broad range of stakeholders, and for conducting “what-if” analyses. The presented research could also support broader aims of developing harmonized sustainability standards for the NRDs industry to adopt and so forward the sustainability transport agenda.

No / Conflicting rankings corresponding to alternative performance criteria and measures are mostly reported in the mono-criterion evaluation of competing distress prediction models (DPMs). To overcome this issue, this study extends the application of the expert system to corporate credit risk and distress prediction through proposing a Multi-criteria Decision Aid (MCDA), namely PROMETHEE II, which provides a multi-criteria evaluation of competing DPMs. In addition, using data on Chinese firms listed on Shanghai and Shenzhen stock exchanges, we perform an exhaustive comparative analysis of the most popular DPMs; namely, statistical, artificial intelligence and machine learning models under both mono-criterion and multi-criteria frameworks. Further, we address two prevailing research questions; namely, "which DPM performs better in predicting distress?" and "will training models with corporate governance indicators (CGIs) enhance the performance of models?”; and discuss our findings. Our multi-criteria ranking suggests that non-parametric DPMs outperform parametric ones, where random forest and bagging CART are among the best machine learning DPMs. Further, models fed with CGIs as features outperform those fed without CGIs.

<p>The purpose of this thesis is to develop an integrated model which involves creative and analytical features for designing a cost effective logistics centre layout on operational level, with respect to time and space utilization. Engineering methods, creative skills, simulation and multi-criteria decision making methods were integreted in the  developed model. The model has been implemented and validated in Oskarshamn Intralog, which is a sister company of Scania. After applying the model in the case company, three different layout concepts were generated based on engineering and simulation techniques. These concepts were evaluated from utilization of space, time and flexibility aspects. Furthermore, multi criteria decision making method was used to select the most cost effective layout concept among these concepts. Different aspects helped to see various effects of warehouse operations on layout design. Simulation was used as a powerful tool to test cycle time within designed concepts. Clearly it was concluded that a combination of two concepts led to reach the expected results as an optimum point among space, time utilization and flexibility which fullfilled the answer to both academical and practical problem</p> / <p><strong> </strong></p><p>Syftet med den här uppsatsen är att utveckla en integrerad modell som inbegriper kreativa och analytiska egenskaper. Modellen ska användas till att designa en kostnadseffektiv planering av anläggningen för ett logistikcentrum på en operationell nivå, med avseende på tid- och lagerplatsutnyttjande. Tekniska metoder, kreativitet, simulering, samt “multi-criteria decision making” är integrerade i modellen. Validering och implementering av modellen skedde på Oskarshamn Intralog, ett systerföretag till Scania. Efter tillämpning av modellen på fallföretaget, genererades tre olika koncept för planering av anläggningen. Koncepten utvärderades utifrån utnyttjande av plats, tid, samt flexibilitet. Dessutom har metoden “multi-criteria decision making” använts för att selektera det mest kostnadseffektiva av de tre koncepten. Olika aspekter på tid- och lagerplatsutnyttjande, samt flexibilitet bidrog till att se olika effekter på lagerhantering. Simuleringar genomfördes för att testa cykeltiden i de utvecklade koncepten. Slutsatsen är att en kombination av två koncept ledde till det förväntade resultatet; en optimal punkt för tid- och lagerplatsutnyttjande, samt flexibilitet, vilket uppfyller svar till de akademiska och praktiska problemen</p>

The purpose of this thesis is to develop an integrated model which involves creative and analytical features for designing a cost effective logistics centre layout on operational level, with respect to time and space utilization. Engineering methods, creative skills, simulation and multi-criteria decision making methods were integreted in the  developed model. The model has been implemented and validated in Oskarshamn Intralog, which is a sister company of Scania. After applying the model in the case company, three different layout concepts were generated based on engineering and simulation techniques. These concepts were evaluated from utilization of space, time and flexibility aspects. Furthermore, multi criteria decision making method was used to select the most cost effective layout concept among these concepts. Different aspects helped to see various effects of warehouse operations on layout design. Simulation was used as a powerful tool to test cycle time within designed concepts. Clearly it was concluded that a combination of two concepts led to reach the expected results as an optimum point among space, time utilization and flexibility which fullfilled the answer to both academical and practical problem / Syftet med den här uppsatsen är att utveckla en integrerad modell som inbegriper kreativa och analytiska egenskaper. Modellen ska användas till att designa en kostnadseffektiv planering av anläggningen för ett logistikcentrum på en operationell nivå, med avseende på tid- och lagerplatsutnyttjande. Tekniska metoder, kreativitet, simulering, samt “multi-criteria decision making” är integrerade i modellen. Validering och implementering av modellen skedde på Oskarshamn Intralog, ett systerföretag till Scania. Efter tillämpning av modellen på fallföretaget, genererades tre olika koncept för planering av anläggningen. Koncepten utvärderades utifrån utnyttjande av plats, tid, samt flexibilitet. Dessutom har metoden “multi-criteria decision making” använts för att selektera det mest kostnadseffektiva av de tre koncepten. Olika aspekter på tid- och lagerplatsutnyttjande, samt flexibilitet bidrog till att se olika effekter på lagerhantering. Simuleringar genomfördes för att testa cykeltiden i de utvecklade koncepten. Slutsatsen är att en kombination av två koncept ledde till det förväntade resultatet; en optimal punkt för tid- och lagerplatsutnyttjande, samt flexibilitet, vilket uppfyller svar till de akademiska och praktiska problemen

L'accroissement et la diversification des services offerts par les systèmes informatiques modernes rendent la tâche de sécuriser ces systèmes encore plus complexe. D'une part, l'évolution du nombre de services système accroît le nombre des vulnérabilités qui peuvent être exploitées par des attaquants afin d'atteindre certains objectifs d'intrusion. D'autre part, un système de sécurité moderne doit assurer un certain niveau de performance et de qualité de service tout en maintenant l'état de sécurité. Ainsi, les systèmes de sécurité modernes doivent tenir compte des exigences de l'utilisateur au cours du processus de sécurité. En outre, la réaction dans des contextes critiques contre une attaque après son exécution ne peut pas toujours remédier à ses effets néfastes. Dans certains cas, il est essentiel que le système de sécurité soit en avance de phase par rapport à l'attaquant et de prendre les mesures nécessaires pour l'empêcher d'atteindre son objectif d'intrusion. Nous soutenons dans cette thèse que le processus de sécurité doit suivre un raisonnement intelligent qui permet au système de prévoir les attaques qui peuvent se produire par corrélation à une alerte détectée et d'appliquer les meilleures contre-mesures possibles. Nous proposons une approche qui génère des scénarios potentiels d'attaque qui correspondent à une alerte détectée. Ensuite, nous nous concentrons sur le processus de génération d'un ensemble approprié de contre-mesures contre les scénarios d'attaque générés. Un ensemble généré des contre-mesures est considéré comme approprié dans l'approche proposée s'il présente un ensemble cohérent et il satisfait les exigences de l'administrateur de sécurité (par exemple, la disponibilité). Nous soutenons dans cette thèse que le processus de réaction peut être considéré comme un débat entre deux agents. D'un côté, l'attaquant choisit ses arguments comme étant un ensemble d'actions pour essayer d'atteindre un objectif d'intrusion, et de l'autre côté l'agent défendant la cible choisit ses arguments comme étant un ensemble de contre-mesures pour bloquer la progression de l'attaquant ou atténuer les effets de l'attaque. D'autre part, nous proposons une approche basée sur une méthode d'aide à la décision multicritère. Cette approche assiste l'administrateur de sécurité lors de la sélection des contre-mesures parmi l'ensemble approprié des contre-mesures générées à partir de la première approche. Le processus d'assistance est basé sur l'historique des décisions de l'administrateur de sécurité. Cette approche permet également de sélectionner automatiquement des contre-mesures appropriées lorsque l'administrateur de sécurité est dans l'incapacité de les sélectionner (par exemple, en dehors des heures de travail, par manque de connaissances sur l'attaque). Enfin, notre approche est implémentée et testée dans le cadre des systèmes automobiles / The growth and diversity of services offered by modern systems make the task of securing these systems a complex exercise. On the one hand, the evolution of the number of system services increases the risk of causing vulnerabilities. These vulnerabilities can be exploited by malicious users to reach some intrusion objectives. On the other hand, the most recent competitive systems are those that ensure a certain level of performance and quality of service while maintaining the safety state. Thus, modern security systems must consider the user requirements during the security process.In addition, reacting in critical contexts against an attack after its execution can not always mitigate the adverse effects of the attack. In these cases, security systems should be in a phase ahead of the attacker in order to take necessary measures to prevent him/her from reaching his/her intrusion objective. To address those problems, we argue in this thesis that the reaction process must follow a smart reasoning. This reasoning allows the system, according to a detected attack, to preview the related attacks that may occur and to apply the best possible countermeasures. On the one hand, we propose an approach that generates potential attack scenarios given a detected alert. Then, we focus on the generation process of an appropriate set of countermeasures against attack scenarios generated among all system responses defined for the system. A generated set of countermeasures is considered as appropriate in the proposed approach if it presents a coherent set (i.e., it does not contain conflictual countermeasures) and it satisfies security administrator requirements (e.g., performance, availability). We argue in this thesis that the reaction process can be seen as two agents arguing against each other. On one side the attacker chooses his arguments as a set of actions to try to reach an intrusion objective, and on the other side the agent defending the target chooses his arguments as a set of countermeasures to block the attacker's progress or mitigate the attack effects. On the other hand, we propose an approach based on a recommender system using Multi-Criteria Decision Making (MCDM) method. This approach assists security administrators while selecting countermeasures among the appropriate set of countermeasures generated from the first approach. The assistance process is based on the security administrator decisions historic. This approach permits also, to automatically select appropriate system responses in critical cases where the security administrator is unable to select them (e.g., outside working hours, lack of knowledge about the ongoing attack). Finally, our approaches are implemented and tested in the automotive system use case to ensure that our approaches implementation successfully responded to real-time constraints.