Analysis of the efficiency of the linearization techniques for solving multi-objective linear fractional programming problems by goal programming

This paper presents and analyzes the applicability of three linearization techniques used for solving multi-objective linear fractional programming problems using the goal programming method. The three linearization techniques are: (1) Taylor’s polynomial linearization approximation, (2) the method of variable change, and (3) a modification of the method of variable change proposed in [20]. All three linearization techniques are presented and analyzed in two variants: (a) using the optimal value of the objective functions as the decision makers’ aspirations, and (b) the decision makers’ aspirations are given by the decision makers. As the criteria for the analysis we use the efficiency of the obtained solutions and the difficulties the analyst comes upon in preparing the linearization models. To analyze the applicability of the linearization techniques incorporated in the linear goal programming method we use an example of a financial structure optimization problem

A goal programming procedure for solving fuzzy multiobjective fractional linear programming problems

This paper presents a modification of Pal, Moitra and Maulik\u27s goal programming procedure for fuzzy multiobjective linear fractional programming problem solving. The proposed modification of the method allows simpler solving of economic multiple objective fractional linear programming (MOFLP) problems, enabling the obtained solutions to express the preferences of the decision maker defined by the objective function weights. The proposed method is tested on the production planning example

Prioritization of the launch of ICT products and services through linguistic multi-criteria decision-making

The market launch of new products and services is a basic pillar for large and medium-sized companies in the ICT (Information and Communications Technology) sector. Choosing the right moment for it is usually a differentiating factor in terms of competition, since it is a source of competitive advantage. There are several mechanisms and strategies to address this problem from the market perspective. However, the criteria of the different actors involved – managers, sales representatives, experts, etc. – coexist in the corporate sphere and they often differ, causing difficulties in priority setting processes in the launch of a product or service. The assessment of the prioritization of these criteria is usually expressed in natural language, thus adding a great deal of uncertainty. Fuzzy linguistic models have proved to be an efficient tool for managing the intrinsic uncertainty of this type of information. This paper presents a linguistic multi-criteria decision-making model, able to reconcile the different requirements and viewpoints existing in the corporate sector when planning the launch of new products and services. The proposed model is based on the fuzzy 2-tuple linguistic model, aimed at managing linguistic data expressing different corporate criteria, without compromising accuracy in the calculation of said data. In order to illustrate this, a practical case study is presented, in which the model is applied for scheduling the launch prioritization of several new products and services by a telecommunications company, within the deadlines set in its strategic planning.The authors would like to acknowledge the financial support received from the European Regional Development Fund (ERDF) for the Research Projects TIN2016-75850-R, TIN2016-79484-R and TIN2013-40658-P

Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers

The OWA operator proposed by Yager has been widely used to aggregate experts' opinions or preferences in human decision making. Yager's traditional OWA operator focuses exclusively on the aggregation of crisp numbers. However, experts usually tend to express their opinions or preferences in a very natural way via linguistic terms. These linguistic terms can be modelled or expressed by (type-1) fuzzy sets. In this paper, we define a new type of OWA operator, the type-1 OWA operator that works as an uncertain OWA operator to aggregate type-1 fuzzy sets with type-1 fuzzy weights, which can be used to aggregate the linguistic opinions or preferences in human decision making with linguistic weights. The procedure for performing type-1 OWA operations is analysed. In order to identify the linguistic weights associated to the type-1 OWA operator, type-2 linguistic quantifiers are proposed. The problem of how to derive linguistic weights used in type-1 OWA aggregation given such type of quantifier is solved. Examples are provided to illustrate the proposed concepts. Crown Copyright © 2008

Assessing the readiness to implement lean in healthcare institutions – a case study

We develop a lean readiness framework and an assessment methodology to quantify the readiness of healthcare institutions for implementing lean. We use stakeholder theory and work with a lean implementation team responsible for process improvement in a healthcare group to develop the framework. The framework uses fuzzy based input derived from the stakeholders of the healthcare institution to generate an overall ranking through ideal solution technique. The assessment method derives input from the readiness scores shared by various stakeholders. The ranking suggests future improvement areas to prepare the healthcare institution for a lean implementation project. We provide an alternative perspective of assessing the lean readiness of healthcare institutions before beginning a lean implementation project for both researchers and practitioners. Our research is the first to develop a lean readiness framework for healthcare institutions and demonstrate it using an assessment technique

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR

Fuzzy quality function deployment for aircraft maintenance organizations

In this thesis, Quality Function Deployment for aircraft maintenance organizations is considered. Assessment and evaluation of quality management in aircraft maintenance organizations is the key to ensure safety, reliability, and the assurance of quality. At present, companies around the world have an absolute need for quality management systems in order to help them to develop and manage better their activities. Improving the way in which organizations handle their organizational management plays a major role in raising the standard of the quality of the product or the quality of the service they deliver. The challenge of implementing quality approaches in the management of aircraft maintenance organizations is appealing since it is recognized to save time and money. As a result, the organization can become more efficient, more competitive in its domain and finally more profitable. Quality management is, therefore, an essential function for maintaining and improving the quality of the services and products provided by aircraft maintenance organizations. First necessary background and theoretical knowledge on aircraft maintenance organizations and quality management is presented in detail. This is achieved by performing an analysis of the needs and the means for improving quality in the maintenance activities. The proposed analysis approach is a combination of Quality Function Deployment, and Fuzzy Logic theory. The Quality Function Deployment is used as an analysis tool to translate the customer needs and requirements into service features. The Quality Function Deployment involves the construction of a matrix structure which allows the assessment and ranking of different course of action with respect to quality. Since many opinions from experts are expressed in linguistic terms it appeared that fuzzy logic could improve this analysis process. Then, the final part of the thesis is devoted to the development of a fuzzy quality function deployment. The proposed analysis approach is then illustrated in the case of aircraft maintenance organizations where the objective is to increase fleet availability, maintain aircraft reliability, decrease servicing time, and limit investment costs.--------------------------------------------------------------------------------------------------------Dans cette thèse, le déploiement de la fonction de la qualité pour l'organisation de l'entretien des avions est considérée. L'évaluation de la gestion de la qualité dans les organismes de maintenance des avions est la clé pour garantir la sécurité, la fiabilité et l'assurance de la qualité. De nos jours, les entreprises partout dans le monde ont un besoin absolu de systèmes, gestion de la qualité afin de les aider à développer et à mieux gérer leurs activités. La façon dont les organisations gèrent leurs gestions de l'organisation joue un rôle majeur dans l'amélioration du niveau de la qualité du produit ou la qualité du service qu'elles fournissent. Le défi de la mise en œuvre de la démarche qualité dans la gestion de la maintenance des avions est important car il doit conduire à des économies de temps et d'argent. La gestion de la qualité est, par conséquent, une fonction essentielle pour maintenir et améliorer la qualité des services et produits offerts par les organismes de maintenance des avions. Dans cette thèse les prés requis et connaissances théoriques sur l'organisation de la maintenance et la gestion de la qualité sont présentés en détail. Ceci est réalisé en effectuant une analyse des besoins et des moyens pour améliorer la qualité dans les activités d'entretien. L'approche d'analyse proposée est une combinaison du déploiement de la fonction de la qualité et de la Logique Floue. Le déploiement de la fonction de la qualité est utilisé comme un outil d'analyse pour traduire les besoins des clients et les besoins en qualité des services. Le déploiement de la fonction de la qualité comprend la construction d'une structure matricielle permettant d’évaluer et de comparer les différents plans d’action. Puisque de nombreuses opinions d'experts sont exprimées en termes linguistiques, il semble que la Logique Floue pourrait améliorer ce processus d'analyse. La dernière partie de cette thèse est consacrée à l'élaboration du déploiement de la fonction de la qualité dans le cadre de la Logique Floue. L'approche d'analyse proposée est ensuite illustrée dans le cas de l'organisation de l'entretien d’une flotte d’avions. L'objectif est d'augmenter la disponibilité de la flotte, de maintenir sa fiabilité, de diminuer le temps du service de maintenance, de limiter les coûts d'investissemen