Implementasi Algoritma Cheapest Insertion Heuristic (CIH) dalam Penyelesaian Travelling Salesman Problem (TSP)

Traveling salesman problem (TSP) is the problem of a salesman to visit the city of each city connected to each other and there is the weight of travel between the cities so as to form a complete weighted graph. Departing from a certain initial city, a salesman had to visit (n-1) another city exactly once and return on the initial city of departure. The purpose of TSP is to find the route of all cities with minimum total weight.Many algorithms have been found to solve the TSP, one of which is the Cheapest Insertion Heuristic (CIH) algorithm in the process of inserting weighted steps obtained from the equation c (i, k, j) = d (i, k) + d (k, j) - d (i, j). This algorithm provides different travel routes depending on the order of insertion of cities on the subtour in question.In this final project, the writer took the problem of distribution route of mineral water of al-ma'some 240 ml cup type, with vehicle capacity to meet 1200 carton and have different customer / agent demand that is the distance of depot and agent far from each other, distribution costs

Scheduling Optimization And Coordination With Target Tracking Under Heterogeneous Networks In Automated Guided Vehicles (AGVs)

Throughout the development of the multi-AGV systems, prevailing research directions contain improving the performance of individual AGV, optimizing the coordination of multiple AGVs, and enhancing the efficiency of communication among AGVs. Current researchers tend to pay attention to one research direction at a time. There is a lack of research on the overall AGV system design that tackles multiple critical design aspects of the system. This PhD research addresses four key factors of the AGV system which are AGV prototypes, target tracking algorithms, AGVs scheduling optimization and the communication of a multi-AGV system. Extensive field experiments and algorithm optimization are implemented. Comprehensive literature review is conducted to identify the research gap. The proposed solutions cover the following three aspects of the AGV system design including communication between AGVs, AGVs scheduling and computer vision in AGVs.        For AGV communication, a network selection optimization algorithm is presented. An improved method for preventing convolutional neural network (CNN) immune from backdoor attack to ensure a multi-AGV system's communication security is presented. Meanwhile, a transmission framework for a multi-AGV system is presented. Those methods are used to establish a safe and efficient multi-AGV system's communication environment. For AGV scheduling, a multi-robot planning algorithm with quadtree map division for obstacles of irregular shape is presented. In addition, a scheduling optimization platform is presented. These methods are used to make a multi-AGV system have a shorter time delay and decrease the possibility of collision in a multi-robot system.Meanwhile, a scheduling optimization method based on the combination of a handover rule and the A* algorithm is proposed. The system properties that may affect the scheduling performance are also discussed. Finally, the overall performance of the newly integrated scheduling system is compared with other scheduling systems to validate its superiority and shortcomings in different corresponding work scenarios. Computer vision in AGV is investigated in detail. To improve an individual AGV's performance, an improved Camshift Algorithm has been proposed and applied to AGV prototypes. Furthermore, three deep learning models are tested under specific environments. In addition, based on the designed algorithm, the AGV prototype is able to make a convergent prediction of the pixels in the target area after the first detection of the object. Relative coordinates of the target can be located more accurately in less time. As tested in the experiments, the system architecture and new algorithm lead to reduced hardware cost, shorter time delay, improved robustness, and higher accuracy in tracking.        With the three design aspects in mind, a novel method for real-time visual tracking and distance measurement is proposed. Tracking and collision avoidance functions are tested in the designed multi-AGV prototype system. Detailed design procedure, numerical analysis of the measurement data and recommendations for further improvement of the system design are presented

An Investigation on Benefit-Cost Analysis of Greenhouse Structures in Antalya

Significant population increase across the world, loss of cultivable land and increasing demand for food put pressure on agriculture. To meet the demand, greenhouses are built, which are, light structures with transparent cladding material in order to provide controlled microclimatic environment proper for plant production. Conceptually, greenhouses are similar with manufacturing buildings where a controlled environment for manufacturing and production have been provided and proper spaces for standardized production processes have been enabled. Parallel with the trends in the world, particularly in southern regions, greenhouse structures have been increasingly constructed and operated in Turkey. A significant number of greenhouses are located at Antalya. The satellite images demonstrated that for over last three decades, there has been a continuous invasion of greenhouses on all cultivable land. There are various researches and attempts for the improvement of greenhouse design and for increasing food production by decreasing required energy consumption. However, the majority of greenhouses in Turkey are very rudimentary structures where capital required for investment is low, but maintenance requirements are high when compared with new generation greenhouse structures. In this research paper, life-long capital requirements for construction and operation of greenhouse buildings in Antalya has been investigated by using benefit-cost analysis study

Knowledge Capturing in Design Briefing Process for Requirement Elicitation and Validation

Knowledge capturing and reusing are major processes of knowledge management that deal with the elicitation of valuable knowledge via some techniques and methods for use in actual and further studies, projects, services, or products. The construction industry, as well, adopts and uses some of these concepts to improve various construction processes and stages. From pre-design to building delivery knowledge management principles and briefing frameworks have been implemented across project stakeholders: client, design teams, construction teams, consultants, and facility management teams. At pre-design and design stages, understanding the client’s needs and users’ knowledge are crucial for identifying and articulating the expected requirements and objectives. Due to underperforming results and missed goals and objectives, many projects finish with highly dissatisfied clients and loss of contracts for some organizations. Knowledge capturing has beneficial effects via its principles and methods on requirement elicitation and validation at the briefing stage between user, client and designer. This paper presents the importance and usage of knowledge capturing and reusing in briefing process at pre-design and design stages especially the involvement of client and user, and explores the techniques and technologies that are usable in briefing process for requirement elicitation

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen