Mohd Sharifuddin Ahmad

Solving vehicle routing problem by using improved genetic algorithm for optimal solution

Abstract Context The Vehicle Routing Problem (VRP) has numerous applications in real life. It clarifies in a wide area of transportation and distribution such as transportation of individuals and items, conveyance service and garbage collection. Thus, an appropriate selecting of vehicle routing has an extensive influence role to improve the economic interests and appropriateness of logistics planning. Problem In this study the problem is as follows: Universiti Tenaga Nasional (UNITEN) has eight buses which are used for transporting students within the campus. Each bus starts from a main location at different times every day. The bus picks up students from eight locations inside the campus in two different routes and returns back to the main location at specific times every day, starting from early morning until the end of official working hours, on the following conditions: Every location will be visited once in each route and the capacity of each bus is enough for all students included in each route. Objectives Our paper attempt to find an optimal route result for VRP of UNITEN by using genetic algorithm. To achieve an optimal solution for VRP of UNITEN with the accompanying targets: To reduce the time consuming and distance for all paths. which leads to the speedy transportation of students to their locations, to reduce the transportation costs such as fuel utilization and additionally the vehicle upkeep costs, to implement the Capacitated Vehicle Routing Problem (CVRP) model for optimizing UNITEN’s shuttle bus services. To implement the algorithm which can be used and applied for any problems in the like of UNITEN VRP. Approach The Approach has been presented based on two phases: firstly, find the shortest route for VRP to help UNITEN University reduce student’s transportation costs by genetic algorithm is used to solve this problem as it is capable of solving many complex problems; secondly, identify The CVRP model is implemented for optimizing UNITEN shuttle bus services. Finding The findings outcome from this study have shown that: (1) A comprehensive listed of active GACVRP; (2) Identified and established an evaluation criterion for GACVRP of UNITEN; (3) Highlight the methods, based on hybrid crossover operation, for selecting the best way (4) genetic algorithm finds a shorter distance for route A and route B. The proportion of reduction the distance for each route is relatively short, but the savings in the distance becomes greater when calculating the total distances traveled by all buses daily or monthly. This applies also to the time factor that has been reduced slightly based on the rate of reduction in the distances of the routes.

Using Genetic Algorithm for Traffic Light Control System with a Pedestrian Crossing

In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.

Agents of Things (AoT): An intelligent operational concept of the Internet of Things (IoT)

In this conceptual paper, we review the definitions, characteristics, and architecture of the Internet of Things (IoT) concept. We then identify the deficiencies of the IoT concept, analyze them, and discover the issue of lack of reasoning and intelligence in the IoT concept. We propose a solution to augment the IoT with intelligent software agents resulting in a new concept called the Agents of Things (AoT). The paper presents the AoT architecture and a scenario for one application of the proposed concept. Finally, it discusses the benefits of implementing AoT concept to solve real world issues and the future work.

Certainty, trust and evidence

We assume a group of agents, in which a process of opinion gathering takes place.We examine the values of agents reputation, trust and certainty.Confidence value for agents depend on the values of trust and certainty.Increasing the importance of trust increases the weight of trust in the confidences value calculations.Agents trust or agents certainty alone does not affect agents confidence value. Introducing confidence in multi-agent systems gives agents a form of control in making decisions and helps to improve the decision making process in such systems. Consequently, modeling confidence of agents is important in heterogeneous agent communities. The inability to detect an agents confidence can be a reason for inaccurate decision. Several weaknesses have been found in current trust and confidence models in multi-agent systems. Current models propose that the trust of an agent depends on its reputation, past experience, and observations on its behavior. This paper presents another approach to agent-based confidence modeling. Initially, it integrates two confidence requirements, namely, trust and certainty. To further strengthen the model, we include evidence as an additional requirement to the model by which trust and certainty of an agent can be verified. This paper establishes bisection between trust, certainty, and evidence spaces. The modeling mechanism eliminates untrusted opinions, since such certainty level might not be valuable in all states. The proposed technique also separates the global confidence scheme from the local confidence scheme, so as to provide greater reliability for confidence detection.

A Review of Norms and Normative Multiagent Systems

Norms and normative multiagent systems have become the subjects of interest for many researchers. Such interest is caused by the need for agents to exploit the norms in enhancing their performance in a community. The term norm is used to characterize the behaviours of community members. The concept of normative multiagent systems is used to facilitate collaboration and coordination among social groups of agents. Many researches have been conducted on norms that investigate the fundamental concepts, definitions, classification, and types of norms and normative multiagent systems including normative architectures and normative processes. However, very few researches have been found to comprehensively study and analyze the literature in advancing the current state of norms and normative multiagent systems. Consequently, this paper attempts to present the current state of research on norms and normative multiagent systems and propose a norms life cycle model based on the review of the literature. Subsequently, this paper highlights the significant areas for future work.

Emergence of social intelligence in social network: A quantitative analysis for agent-mediated PKM processes

Social intelligence has been coined by authors in many aspects, with one of them being the sociability characteristics of a software agent in performing tasks over social network. This concept has been expanded from personal knowledge management (PKM) frameworks using agent mediation, where intelligent agents are assigned with tasks to assist their human counterparts. In recent studies, PKM processes are understood to be a series of getting knowledge, analysing/understanding knowledge, sharing/publishing knowledge and connecting to others for knowledge over the Internet and social network. The critical issue of this concept involves identifying and ‘locating’ knowledge experts for further enlightenment of ones personal knowledge. Taking into considerations the advantages of social network and the similarities between PKM processes and Nonakas SECI model, the emergence of social intelligence are investigated in this paper by analysing the responses from a questionnaire survey on PKM processes over the social network. This paper also discusses the limitations of this research vis-à-vis the current situation where e-mail is still seen as the only reliable way to manage personal knowledge. It then recommends future works in the realm of social intelligence, involving software agents.

A Dynamic Measurement of Agent Autonomy in the Layered Adjustable Autonomy Model

In a dynamically interactive systems that contain a mix of humans’ and software agents’ intelligence, managing autonomy is a challenging task. Giving an agent a complete control over its autonomy is a risky practice while manually setting the agent’s autonomy level is an inefficient approach. In this paper, we propose an autonomy measurement mechanism and its related formulae for the Layered Adjustable Autonomy (LAA) model. Our model provides a mechanism that optimizes autonomy distribution, consequently, enabling global control of the autonomous agents that guides or even withholds them whenever necessary. This is achieved by formulating intervention rules on the agents’ decision-making capabilities through autonomy measurement criteria. Our aim is to create an autonomy model that is flexible and reliable.

A conceptual model of layered adjustable autonomy

Autonomy and autonomous agents are currently the most researched topics in autonomous systems. Issues like autonomy adjustment, autonomy level, and the required degree of autonomy to be performed are investigated. Abstracting an autonomy model poses the problem of identifying specific aspects that merit an autonomous system. In this paper, we propose another model of autonomy that conceptualizes autonomy as a spectrum, which is constructed in a layered structure of a multi-agent environment called Layered Adjustable Autonomy (LAA). The autonomy spectrum of the LAA is divided into adjustable-leveled layers. Each of which has distinct attributes and properties that assist an agent in managing the influences of the environment during its decision-making process. The LAA structure is designed to endorse an agent’s qualification to make a decision by setting the degree of autonomy to the agent’s choice of decision-making. An Autonomy Analysis Module (AAM) is also proposed to control and delegate the agent’s actions at specific autonomy levels. Hence, the AAM determines the threshold of the agent autonomy level to act in its qualified layer. Ultimately, the proposed LAA model will be implemented on an air drone for the purpose of testing and refinement.

A Dynamically Adjustable Autonomic Agent Framework

The design and development of autonomous software agents is still a challenging task and needs further investigation. Giving an agent the maximum autonomous capabilities may not necessarily produce satisfactory agent behavior. Consequently, adjustable autonomy has become the hallmark of autonomous systems development that influences an agent to exhibit satisfactory behavior. To perform such influences, however, a dynamic adjustment mechanism is needed to be configured. The influences are costly in time and implementation especially for systems with time-critical domain. They might negatively influence agent decisions and cause system disturbance. In this paper, we propose a framework to govern an agent autonomy adjustment and minimize system disturbance. The main components of the proposed framework are the Planner, Scheduler and Controller (PSC) that conform to the current trends in automated systems. Two modules are also suggested which are Autonomy Analysis Module (AAM) and Situation Awareness Module (SAM). They are accordingly used to distribute the autonomy and provide balance to the system so that it’s local and global desires do not conflict.

Norms Detection and Assimilation in Multi-agent Systems: A Conceptual Approach

In this paper, we propose a technique for a software agent to detect the norms of a community of agents and assimilate its behavior to comply with the local normative protocol, failing which, the agent is refused services and resources. In this technique, the software agent is equipped with an algorithm, which detects and analyzes the normative interactions between local agents. When the detection is successful, it launches another algorithm to request for its assimilation to the local normative protocol, indicating its acceptance by the group of local agents.