Smart Growth Principles Combined with Fuzzy AHP and DEA Approach to the Transit-oriented Development (TOD) Planning in Urban Transportation Systems

The research for a land use and transportation planning has always been an important study area among the urban planning field. Since the 20th century, automobiles had become the main media as the transportation vehicle. However, the automobile-oriented development (AOD) also caused the sever urban sprawl problem during the past years. In order to reduce the problems of urban sprawl, the Smart Growth concepts have been proposed and applied to transportation planning process. In recent years, with the up to date sustainable development concept, the transit-oriented development (TOD) model has become one of the novel transport planning strategies utilized to improve the urban environment by means of Smart Growth principles. This study tries to integrate smart growth principles into the urban transportation planning development strategies and utilize objective scientific method to the empirical study. This study will include the following sections. First of all, we try to study and classify the category of smart growth principles based on literature review. Followed by applying fuzzy Delphi technique (FDT) to obtain individual expert’s opinions and to screen the most important criteria of proposed principles in our research. And then the empirical study of Taipei Metro Transit System will be demonstrated to show the application of our proposed methodology. Finally, the utilization of data envelopment analysis (DEA) model combined with assurance region analysis will be applied to select the most suitable MRT stations as the suggested strategies for public sectors. Keywords: Smart Growth, Transit-oriented Development (TOD), Fuzzy Delphi Technique (FDT), Data Envelopment Analysis (DEA

Strategic Trip Planning: Striking a Balance Between Competition and Cooperation

In intelligent transportation systems, cooperative mobility planning is considered to be one of the challenging problems. Mobility planning as it stands today is an in- dividual decision-making effort that takes place in an environment governed by the collective actions of various competing travellers. Despite the extensive research on mobility planning, a situation in which multiple behavioural-driven travellers partic- ipate in a cooperative endeavour to help each other optimize their objectives has not been investigated. Furthermore, due to the inherent multi-participant nature of the mobility problem, the existing solutions fail to produce ground truth optimal mobil- ity plans in the practical sense - despite their claimed and well proven theoretical optimality. This thesis proposes a multi-module team mobility planning framework to address the team trip planning problem with a particular emphasis on modelling the inter- action between behaviour-driven rational travellers. The framework accommodates the travellers’ individual behaviours, preferences, and goals in cooperative and com- petitive scenarios. The individual behaviours of the travellers and their interaction processes are viewed as a team trip planning game. For this game, a theoretical anal- ysis is presented, which includes an analysis of the existence and the balancedness of the final solution. The proposed framework is composed of three principal modules: cooperative trip planning, team formation, and traveller-centric trip planning (TCTP). The cooper- ative trip planning module deploys a bargaining model to manage conflicts between the travellers that could occur in their endeavour to discover a general, satisfactory solution. The number of players and their interaction process is controlled by the team formation module. The TCTP module adopts an alternative perspective to the individualized trip-planning problem in the sense that it is being behavioural driven problem. This allows for multitudes of traveler centric objectives and constraints, as well as aspects of the environment as they pertain to the traveller’s preferences, to be incorporated in the process. Within the scope of the team mobility planning frame- work, the TCTP is utilized to supply the travellers with personalized strategies that are incorporated in the cooperative game. The concentration problem is used in this thesis to demonstrate the effectiveness of the TCTP module as a behavioural-driven trip planner. Finally, to validate the theoretical set-up of the team trip planning game, we introduce the territory sharing problem for social taxis. We use the team mobility framework as a basis to solve the problem. Furthermore, we present an argument for the convergence and the efficiency of a coarse correlated equilibrium. In addition to the validation of a variety of theoretical concepts, the territory sharing problem is used to demonstrate the applicability of the proposed framework in dealing with cooperative mobility planning problems

Game Theory Relaunched

The game is on. Do you know how to play? Game theory sets out to explore what can be said about making decisions which go beyond accepting the rules of a game. Since 1942, a well elaborated mathematical apparatus has been developed to do so; but there is more. During the last three decades game theoretic reasoning has popped up in many other fields as well - from engineering to biology and psychology. New simulation tools and network analysis have made game theory omnipresent these days. This book collects recent research papers in game theory, which come from diverse scientific communities all across the world; they combine many different fields like economics, politics, history, engineering, mathematics, physics, and psychology. All of them have as a common denominator some method of game theory. Enjoy

On the nonemptiness of approximate cores of large games

We provide a new proof of the nonemptiness of approximate cores of games with many players of a finite number of types. Earlier papers in the literature proceed by showing that, for games with many players, equal-treatment cores of their “balanced cover games,” which are nonempty, can be approximated by equal-treatment \varepsilon ? -cores of the games themselves. Our proof is novel in that we develop a limiting payoff possibilities set and rely on a fixed point theorem

A Game-Theoretic Approach to Strategic Resource Allocation Mechanisms in Edge and Fog Computing

With the rapid growth of Internet of Things (IoT), cloud-centric application management raises questions related to quality of service for real-time applications. Fog and edge computing (FEC) provide a complement to the cloud by filling the gap between cloud and IoT. Resource management on multiple resources from distributed and administrative FEC nodes is a key challenge to ensure the quality of end-user’s experience. To improve resource utilisation and system performance, researchers have been proposed many fair allocation mechanisms for resource management. Dominant Resource Fairness (DRF), a resource allocation policy for multiple resource types, meets most of the required fair allocation characteristics. However, DRF is suitable for centralised resource allocation without considering the effects (or feedbacks) of large-scale distributed environments like multi-controller software defined networking (SDN). Nash bargaining from micro-economic theory or competitive equilibrium equal incomes (CEEI) are well suited to solving dynamic optimisation problems proposing to ‘proportionately’ share resources among distributed participants. Although CEEI’s decentralised policy guarantees load balancing for performance isolation, they are not faultproof for computation offloading. The thesis aims to propose a hybrid and fair allocation mechanism for rejuvenation of decentralised SDN controller deployment. We apply multi-agent reinforcement learning (MARL) with robustness against adversarial controllers to enable efficient priority scheduling for FEC. Motivated by software cybernetics and homeostasis, weighted DRF is generalised by applying the principles of feedback (positive or/and negative network effects) in reverse game theory (GT) to design hybrid scheduling schemes for joint multi-resource and multitask offloading/forwarding in FEC environments. In the first piece of study, monotonic scheduling for joint offloading at the federated edge is addressed by proposing truthful mechanism (algorithmic) to neutralise harmful negative and positive distributive bargain externalities respectively. The IP-DRF scheme is a MARL approach applying partition form game (PFG) to guarantee second-best Pareto optimality viii | P a g e (SBPO) in allocation of multi-resources from deterministic policy in both population and resource non-monotonicity settings. In the second study, we propose DFog-DRF scheme to address truthful fog scheduling with bottleneck fairness in fault-probable wireless hierarchical networks by applying constrained coalition formation (CCF) games to implement MARL. The multi-objective optimisation problem for fog throughput maximisation is solved via a constraint dimensionality reduction methodology using fairness constraints for efficient gateway and low-level controller’s placement. For evaluation, we develop an agent-based framework to implement fair allocation policies in distributed data centre environments. In empirical results, the deterministic policy of IP-DRF scheme provides SBPO and reduces the average execution and turnaround time by 19% and 11.52% as compared to the Nash bargaining or CEEI deterministic policy for 57,445 cloudlets in population non-monotonic settings. The processing cost of tasks shows significant improvement (6.89% and 9.03% for fixed and variable pricing) for the resource non-monotonic setting - using 38,000 cloudlets. The DFog-DRF scheme when benchmarked against asset fair (MIP) policy shows superior performance (less than 1% in time complexity) for up to 30 FEC nodes. Furthermore, empirical results using 210 mobiles and 420 applications prove the efficacy of our hybrid scheduling scheme for hierarchical clustering considering latency and network usage for throughput maximisation.Abubakar Tafawa Balewa University, Bauchi (Tetfund, Nigeria