Fuzzy decision making system and the dynamics of business games

Effective and efficient strategic decision making is the backbone for the success of a business organisation among its competitors in a particular industry. The results of these decision making processes determine whether the business will continue to survive or not. In this thesis, fuzzy logic (FL) concepts and game theory are being used to model strategic decision making processes in business organisations. We generally modelled competition by business organisations in industries as games where each business organization is a player. A player formulates his own decisions by making strategic moves based on uncertain information he has gained about the opponents. This information relates to prevailing market demand, cost of production, marketing, consolidation efforts and other business variables. This uncertain information is being modelled using the concept of fuzzy logic. In this thesis, simulation experiments were run and results obtained in six different settings. The first experiment addresses the payoff of the fuzzy player in a typical duopoly system. The second analyses payoff in an n-player game which was used to model a perfect market competition with many players. It is an extension of the two-player game of a duopoly market which we considered in the first experiment. The third experiment used and analysed real data of companies in a case study. Here, we chose the competition between Coca-cola and PepsiCo companies who are major players in the beverage industry. Data were extracted from their published financial statements to validate our experiment. In the fourth experiment, we modelled competition in business networks with uncertain information and varying level of connectivity. We varied the level of interconnections (connectivity) among business units in the business networks and investigated how missing links affect the payoffs of players on the networks. We used the fifth experiment to model business competition as games on boards with possible constraints or restrictions and varying level of connectivity on the boards. We also investigated this for games with uncertain information. We varied the level of interconnections (connectivity) among the nodes on the boards and investigated how these a ect the payoffs of players that played on the boards. We principally used these experiments to investigate how the level of availability of vital infrastructures (such as road networks) in a particular location or region affects profitability of businesses in that particular region. The sixth experiment contains simulations in which we introduced the fuzzy game approach to wage negotiation in managing employers and employees (unions) relationships. The scheme proposes how employers and employees (unions) can successfully manage the deadlocks that usually accompany wage negotiations. In all cases, fuzzy rules are constructed that symbolise various rules and strategic variables that firms take into consideration before taken decisions. The models also include learning procedures that enable the agents to optimize these fuzzy rules and their decision processes. This is the main contribution of the thesis: a set of fuzzy models that include learning, and can be used to improve decision making in business

Game theoretic optimisation in process and energy systems engineering: A review

Game theory is a framework that has been used by various research fields in order to represent dynamic correlation among stakeholders. Traditionally, research within the process and energy systems engineering community has focused on the development of centralised decision making schemes. In the recent years, decentralised decision-making schemes have attracted increasing attention due to their ability to capture multi-stakeholder dynamics in a more accurate manner. In this article, we survey how centralised and decentralised decision making has been facilitated by game theoretic approaches. We focus on the deployment of such methods in process systems engineering problems and review applications related to supply chain optimisation problems, design and operations, and energy systems optimisation. Finally, we analyse different game structures based on the degree of cooperation and how fairness criteria can be employed to find fair payoff allocations

A comprehensive review of hybrid game theory techniques and multi-criteria decision-making methods

More studies trend to hybrid the game theory technique with the multi-criteria decision-making (MCDM) method to aid real-life problems. This paper provides a comprehensive review of the hybrid game theory technique and MCDM method. The fundamentals of game theory concepts and models are explained to make game theory principles clear to the readers. Moreover, the definitions and models are elaborated and classified to the static game, dynamic game, cooperative game and evolutionary game. Therefore, the hybrid game theory technique and MCDM method are reviewed and numerous applications studied from the past works of literature are highlighted. The result of the previous studies shows that the fundamental elements for both frameworks were studied in various ways with most of the past studies tend to integrate the static game with AHP and TOPSIS methods. Also, the integration of game theory techniques and MCDM methods was studied in various applications such as politics, economy, supply chain, engineering, water management problem, allocation problem and telecommunication network selection. The main contribution of the recent studies of employment between game theory technique and MCDM method are analyzed and discussed in detail which includes static and dynamic games in the non-cooperative game, cooperative game, both non-cooperative and cooperative games and evolutionary gam

Integrated management of chemical processes in a competitive environment

El objetivo general de esta Tesis es mejorar el proceso de la toma de decisiones en la gestión de cadenas de suministro, tomando en cuenta principalmente dos diferencias: ser competitivo considerando las decisiones propias de la cadena de suministro, y ser competitivo dentro de un entorno global. La estructura de ésta tesis se divide en 4 partes principales: La Parte I consiste en una introducción general de los temas cubiertos en esta Tesis (Capítulo 1). Una revisión de la literatura, que nos permite identificar las problemáticas asociadas al proceso de toma de decisiones (Capítulo 2). El Capítulo 3 presenta una introducción de las técnicas y métodos de optimización utilizados para resolver los problemas propuestos en esta Tesis. La Parte II se enfoca en la integración de los niveles de decisión, buscando mejorar la toma de decisiones de la propia cadena de suministro. El Capítulo 4 presenta una formulación matemática que integra las decisiones de síntesis de procesos y las decisiones operacionales. Además, este capítulo presenta un modelo integrado para la toma de decisiones operacionales incluyendo las características del control de procesos. El Capítulo 5 muestra la integración de las decisiones del nivel táctico y el operacional, dicha propuesta está basada en el conocimiento adquirido capturando la información relacionada al nivel operacional. Una vez obtenida esta información se incluye en la toma de decisiones a nivel táctico. Finalmente en el capítulo 6 se desarrolla un modelo simplificado para integrar múltiples cadenas de suministro. El modelo propuesto incluye la información detallada de las entidades presentes en una cadena de suministro (suministradores, plantas de producción, distribuidores y mercados) introduciéndola en un modelo matemático para su coordinación. La Parte III propone la integración explicita de múltiples cadenas de suministro que tienen que enfrentar numerosas situaciones propias de un mercado global. Asimismo, esta parte presenta una nueva herramienta de optimización basada en el uso integrado de métodos de programación matemática y conceptos relacionados a la Teoría de Juegos. En el Capítulo 7 analiza múltiples cadenas de suministro que cooperan o compiten por la demanda global del mercado. El Capítulo 8 incluye una comparación entre el problema resuelto en el Capítulo anterior y un modelo estocástico, los resultados obtenidos nos permiten situar el comportamiento de los competidores como fuente exógena de la incertidumbre típicamente asociada la demanda del mercado. Además, los resultados de ambos Capítulos muestran una mejora sustancial en el coste total de las cadenas de suministro asociada al hecho de cooperar para atender de forma conjunta la demanda disponible. Es por esto, que el Capítulo 9 presenta una nueva herramienta de negociación, basada en la resolución del mismo problema (Capítulo 7) bajo un análisis multiobjetivo. Finalmente, la parte IV presenta las conclusiones finales y una descripción general del trabajo futuro.This Thesis aims to enhance the decision making process in the SCM, remarking the difference between optimizing the SC to be competitive by its own, and to be competitive in a global market in cooperative and competitive environments. The structure of this work has been divided in four main parts: Part I: consists in a general introduction of the main topics covered in this manuscript (Chapter I); a review of the State of the Art that allows us to identify new open issues in the PSE (Chapter 2). Finally, Chapter 3 introduces the main optimization techniques and methods used in this contribution. Part II focuses on the integration of decision making levels in order to improve the decision making of a single SC: Chapter 4 presents a novel formulation to integrate synthesis and scheduling decision making models, additionally, this chapter also shows an integrated operational and control decision making model for distributed generations systems (EGS). Chapter 5 shows the integration of tactical and operational decision making levels. In this chapter a knowledge based approach has been developed capturing the information related to the operational decision making level. Then, this information has been included in the tactical decision making model. In Chapter 6 a simplified approach for integrated SCs is developed, the detailed information of the typical production‐distribution SC echelons has been introduced in a coordinated SC model. Part III proposes the explicit integration of several SC’s decision making in order to face several real market situations. As well, a novel formulation is developed using an MILP model and Game Theory (GT) as a decision making tool. Chapter 7 includes the tactical and operational analysis of several SC’s cooperating or competing for the global market demand. Moreover, Chapter 8 includes a comparison, based on the previous results (MILP‐GT optimization tool) and a two stage stochastic optimization model. Results from both Chapters show how cooperating for the global demand represent an improvement of the overall total cost. Consequently, Chapter 9 presents a bargaining tool obtained by the Multiobjective (MO) resolution of the model presented in Chapter 7. Finally, final conclusions and further work have been provided in Part IV.Postprint (published version

Improving green supply chain performance with Operations Research

Due to increasing greenhouse gas emission as a consequence of the production activities in various industries, managing the supply chain has been a big concern between both scholars and practitioners. Green supplier selection and order allocation is among important topics that managers should pay attention to as the majority of the supply chain costs and emission level during production process depends on the procured material by suppliers. Also, investigating the emission abatement regulations, and interactions between regulator and manufacturers is one of the main concerns of supply chain managers that should be figured out. In the present study, green supply chain problems are taken into account for more investigations. First, a green supplier selection and order allocation model in a closed-loop supply chain considering both environmental and economical criteria, is studied. In this study, one of the carbon emission abatement schemes, cap-and-trade mechanism is proposed. The described problem is modeled as a multi-objective robust optimization (RO) model. Second, the cap-and-trade (C\&T) mechanism is further investigated. The goal of this investigation is to find the best strategy for supply chain parties to maximize their utility as well as minimize the carbon emission. To model the described problem, a stochastic three-player game theoretical model is developed. The results show that the developed models can effectively help decision makers select the most appropriate suppliers, allocate the proper amount of order to each selected supplier, and find optimal strategy of C\&T players. Also, the results show that the uncertainty control approaches used in the presented models are capable of handling the model uncertainties from different sources. Furthermore, this study shows that C\&T outperforms the penalty based systems in terms of the total utility of the supply chain. Moreover, the robustness of the results is proved by sensitivity analyses. Another area that is investigated in this study is the disruption effects on supply chain. Disasters and pandemics like COVID-19 can destroy industries by causing huge disruptions in their supply chains. To control these disruptions, decision-makers need to design resilient supply chains. This study proposes a multi-stage, multi-period resilient green supply chain design model considering six resilient strategies. Disruptions are taken into account in both downstream and upstream directions, causing the ripple effect and bullwhip effect, respectively. To control the mentioned disruptions, and handle uncertainties of parameter estimations, a two-stage stochastic optimization approach is applied. The objectives are to minimize the total cost of disruption and $CO_{2}$ emission considering the cap-and-trade mechanism as a government-issued emission regulation. The proposed decision-making framework and solution approach are validated using a numerical experiment followed by a sensitivity analysis. The results show the optimal structure of the supply chain and the best resilient strategies to mitigate the ripple effect. Moreover, the effect of a decrease in capacity of facilities on the optimal solution and the applied resilient strategies is investigated. This study provides managerial insights to help governments set the proper amount of cap and supply chain managers to predict the demand behaviour of essential and non-essential products in the event of disruptions

Non-cooperative two-echelon supply chains with a focus on social responsibility

open access articleTo cooperate or not is one of the most challenging issues of supply chain management era. If the supply chain is managed optimally, the entire profitability increases. Meanwhile, corporate Social Responsibility (hereafter CSR) is defined as the social and ethical behavior of supply chain members against stakeholders such as shareholders, final customers, employees and executives. Moreover, the observance of the social responsibility obligations is of great importance for consumers and shareholders of companies. The decisions of the supply chain’s members play a direct role in determining the profits of each. These decisions are in conflict with other members in a competitive environment. In this paper, the contradictory variables encompasses the cost resulting from the performance of corporate social responsibility, inventory, shortage, advertising and pricing in a two-level supply chain, consisting a manufacturer and a retailer. After identifying the quantitative variables for measuring the social responsibility using Delphi-Fuzzy methods and Interpretive Structural Modeling, the most important and influential variable of measuring the social responsibility performance (forced labor ratio) has been selected. Subsequently, after modeling the profit function of each player, optimal results were emanated according to the bargaining power of each member and based on Nash and Stackelberg games. Afterwards, with numerical examples, the optimization and sensitivity analysis of social responsibility in each model has been discussed. The results indicate that the profit of manufacturer and retailer reduces by increasing the proportion of forced labor. Based upon Nash equilibrium, the manufacturer’s profit decreases with a slight slope; nonetheless, on retailer and manufacturer leadership models, the profit decreases with a slight increase of the forced labor

Palm biomass supply management : a predictive analysis tool

The flourishing of oil palm industry has always been regarded as a double-edged sword. While it has significantly contributed to the economic growth, it is, nonetheless, disputably unsustainable as it is a land-intensive industry and causing disposal problems by leaving behind massive waste. To strengthening the industry’s competitive advantage and offsetting its drawbacks, this thesis presents a forward-looking framework – Biomass Supply Value Chain (BSVC)– to put emphasis on the value creation for the biomass industry. It aims to enhance the current biomass supply chain by harnessing the emerging technological advancement of artificial intelligence (AI), as well as by incorporating game theory to examine the strategic arrangement of the industry players. The proposed framework is capable of optimising the procurement process in the supply chain management: first, by identifying biomass properties for optimum biomass utilisation through the developed Biomass Characteristic Index (BCI); second, by applying AI into supply chain-related tasks for aiding better decision-making and problem-solving; and third, by adopting game theory in analysing strategic options, and providing appropriate strategies to minimise uncertainty and risk in procurement process. The “value” as suggested in the BSVC does not merely refer to a narrow economic sense, but is an all-encompassing value concerning non-monetary utility values, including sustainability, environmental preservation and the appreciation of the biomass industry

Environmental risk management system design for hazardous waste materials

Hazardous materials can be generally deemed as any material which, because of its quantity, concentration, or physical, chemical, or infectious characteristics, may cause, or pose a substantial or potential hazard to human health or the environment. In the context of "sustainable development", most 'materials' could be deemed to be 'hazardous' at some stage of their lifecycle, i.e. from extraction to final disposal.This PhD study develops a decision support system for engineers and policy makers to help limit environmental burden, by reducing the environmental risk and the associated carbon footprint, from the perspective of 'hazardous' materials in product design, through the application of 'game theory' and 'grey theory' etc, as well as various computational approaches, by helping the designer identify novel solutions or mitigation strategies.The thesis starts by introducing the problem situation of the study and identify the research objectives, as well as previous studies have been reviewed in order to set this study in context.Since it is evident that consumers drive the open market, and their preference may be influenced by the carbon footprint label of products, the decision support system proposes an improved carbon labelling scheme to demonstrate the significance of a product‘s carbon footprint in a more visual way. The prototype of the scheme is derived from the concept of 'tolerability of risk', providing a framework by which judgments can be made as to whether society will accept the risk from hazardous materials.Application of game theory for decision support is a novel approach in this study, which aids decision-making by selecting appropriate strategies for both organisations and policy makers to reduce environmental impact. In this context, a game between manufacturers and government in the field of clean production is generated with various game scenarios to reflect the variation trend of strategic actions, and then developed to discuss the reduction of the inherent risk posed by 'hazardous' materials and carbon emissions on the supply chain network.The 'hierarchy of waste' suggests that the most preferable state for sustainability is prevention or the elimination of waste. Although this is not wholly practicable in real terms, the framework gives the importance to waste minimisation and prevention, especially promotes the cleaner production. In addition to strategy selection for mitigating environmental impact, the decision support system also develops an evaluation methodology for application by engineers to aid decision-making on materials selection, thus to improve the materials performances, promote cleaner production and provide better and sustainable products for public consumption