Generating an initial solution for capacitated vehicle routing problem by using sequential insertion algorithm

This research discussed about the extension of the Vehicle Routing Problem (VRP) called the Capacitated Vehicle Routing Problem (CVRP). CVRP deals with the distribution of goods between depots and customers restricted to a single capacity constraint. The main objective of this research is to construct, allocate and arrange customers among routes designed involving a fleet of homogeneous vehicles. Heuristic method, that is, the Sequential Insertion algorithm will be adapted in generating an initial solution to the problem. Our case study is to solve the CVRP involving 100 customers with limitation that every customers is visited by exactly once with only one vehicle where the total demand on each route must be within the vehicle's capacitylimit. Thus, coding of the Sequential Insertion algorithm based on the developed pseudocodes is completed by using the c++ Language Programming in order to generate the initial solution of the CVRP

A farthest insertion heuristic algorithm for the distance-constrained capacitated vehicle routing problem

The vehicle routing problem (YRP) under distance and capacity constraints involves the design of a set of delivery routes which originate and terminate at a central depot after satisfying the customer demands . Each customer must be served exactly once and by one vehicle, where vehicle capacity and distance limit become the constraints of the problem. In this study of Distance-Constrained Capacitated Vehicle Routing Problem (DCYRP), farthest insertion method is used to construct an initial solution. The method focuses on choosing the farthest customer from the route and then inserts the selected customer into the nearest path which will give the smallest increment of length without violating the distance and capacity constraints. C++ numerical programming is used to code the approach algorithm in order to solve DCYRP which involves large groups of data . Three categorie s of data which are cluster, random and random cluster data are being analyzed by considering different amount of distance and capacity constraints. By utilizing the farthest insert ion method , the number of routes participated and the total distance travelled by the vehicles can be obtained. Based on the computational results acquired, the increasing of the amount of capacity and distance constraints will reduce the number of routes formed as well as the total distance travelled

Coordination of production scheduling and vehicle routing problem with release and due date

This work is concerned with solving the vehicle routing problem (VRP) which takes into account the customer’s release and due date. The problem studied can also be categorized as a non-classical VRP as the departure times of vehicles depend on the dates of orders released from the production line and become available for the distribution process. The problem is investigated through two stages. In the first stage, vehicle routing problem with release and due date (VRPRDD) is treated. At the beginning of the planning, it is assumed that the dates where the customer orders become available are known. A mathematical formulation is developed to represent the problem which solved by several heuristics, i.e. Variable Neighborhood Search (VNS), Large Neighborhood Search (LNS) and Tabu Search (TS). The algorithms are written in C++ and run on a PC computer with an Intel PentiumCore by using 56’s Solomon instances with some modification. Different kinds of vehicle routing problem have been tackled in order to see the performance of proposed heuristics. The results are then compared in order to find the best method which yields the least routing cost solution. From the outcome obtained, VNS is proved to be the best algorithm which generates the least cost solution to our problem. Further investigation has been carried out in stage two which considers the extension of VRPRDD. The coordination of production sequence and vehicle routing (PS-VRPRDD) is the main subject to our problem studied in which the best production sequence will leads to the least routing. Classical decomposition approach, namely Alternateis used which decompose the problems into two sub-problems, i.e. production sequence and vehicle routing. The results proved that effective coordination shows the large potential savings that attract the interest of industrial distributors in optimizing their distribution process in practice

Parameter estimation for a mechanistic model of high dose irradiation damage using Nelder-Mead simplex method and genetic algorithm

Radiation therapy is one of the cancer cells treatments that use high-energy radiation to shrink tumors and kill cancer cells. Radiation therapy kills cancer cells by damaging their DNA directly or creates charged particles within the cells that can in turn damage the DNA. As a side effect of the treatment, the radiation therapy can also damage the normal cell that located at parts of our body. The main goals of radiation therapy are to maximize the damaging of tumors cell and minimize the damage of normal tissue cell. Hence, in this study, we adopt an existing model of high dose irradiation damage. The purpose of this study is to estimate the six parameters of the model which are involved. Two optimization algorithms are used in order to estimate the parameters: Nelder-Mead (NM) simplex method and Genetic Algorithm (GA). Both methods have to achieve the objective function which is to minimize the sum of square error (SSE) between the experimental data and the simulation data. The performances of both algorithms are compared based on the computational time, number of iteration and value of sum of square error. The optimization process is carried out using MATLAB programming built-in functions. The parameters estimation results shown that Nelder-Mead simplex method is more superior compare to Genetic Algorithm for this problem

The impact of personality trait on the relationship of emotional intelligence and self-esteem

Fundamental science of psychology often rooted in diversity theory that touching reality of human and humanity. Theoretical solution alone may not be able to unlock the psychological issues because it is closely related to affective, cognitive and human behaviour in the workplace. In this study, the issues in the workplace are referring to personality, emotional intelligence and self-esteem of employees. The specific purpose of this study was to test the effect of extraversion personality as a moderator towards the relationship of emotional intelligence and self-esteem of employees. A total of 196 civil servants in the Local Authority (LA) have been selected as respondents. Measurement tools that used is Eysenck Personality Questionnaire-Revised Short Form (EPQR-S), Emotional Intelligence Self-Description Inventory (EISDI), and Rosenberg Self-Esteem Scale (RSES). The data was analysed by using the hierarchical regression analysis. The finding shows that the two hypotheses are accepted. From this analysis as well, there was a moderating effect of extraversion personality on the relationship between emotional intelligence (perception and appraisal of emotion, and understanding emotions) with self-esteem of employees. The most important finding shows that extraversion personality serves as moderator when the relationship between emotional intelligence and self-esteem are enhanced if extraversion were on a high level. This is compared with the low levels of extraversion personality that causing on relationship of emotional intelligence with self-esteem more weaker

The impact of personality trait on the relationship of emotional intelligence and self-esteem

Fundamental science of psychology often rooted in diversity theory that touching reality of human and humanity. Theoretical solution alone may not be able to unlock the psychological issues because it is closely related to affective, cognitive and human behaviour in the workplace. In this study, the issues in the workplace are referring to personality, emotional intelligence and self-esteem of employees. The specific purpose of this study was to test the effect of extraversion personality as a moderator towards the relationship of emotional intelligence and self-esteem of employees. A total of 196 civil servants in the Local Authority (LA) have been selected as respondents. Measurement tools that used is Eysenck Personality Questionnaire-Revised Short Form (EPQR-S), Emotional Intelligence Self-Description Inventory (EISDI), and Rosenberg Self-Esteem Scale (RSES). The data was analysed by using the hierarchical regression analysis. The finding shows that the two hypotheses are accepted. From this analysis as well, there was a moderating effect of extraversion personality on the relationship between emotional intelligence (perception and appraisal of emotion, and understanding emotions) with self-esteem of employees. The most important finding shows that extraversion personality serves as moderator when the relationship between emotional intelligence and self-esteem are enhanced if extraversion were on a high level. This is compared with the low levels of extraversion personality that causing on relationship of emotional intelligence with self-esteem more weaker

Linear programming model for investment problem in maximizing the total return

In this paper, we concentrate on the investment problem of fixed deposit (FD). Our problem is to allocate the amount invested to a suitable tenure and obtain the optimal investment. There are two types of maturity that need to be considered which are short-term and long-term. Our objective is to maximize the total return of the total amount invested with a different percentage of annual return. A linear programming (LP) model is proposed to solve this investment problem using scheduling methodology. We conduct a computational experiment of a real case study for one company located in Kuala Lumpur with RM 20.6 million of investment to see the performance of the model by using the Excel Solver Parameter package. The results show that a significant improvement obtains by our model compared to the original investment practice by the company

Detection of brain tumour in 2d MRI: implementation and critical review of clustering-based image segmentation methods

Image segmentation can be defined as segregation or partitioning of images into multiple regions with the same predefined homogeneity criterion. Image segmentation is a crucial process in medical image analysis. This paper explores and investigates several unsupervised image segmentation approaches and their viability and performances in delineating tumour region in contrast enhanced T1-weighted brain MRI (Magnetic Resonance Imaging) scans. First and foremost, raw CE T1-weighted brain MR images are downloaded from a free online database. The images are then pre-processed and undergo an important process called skull stripping. Then, image segmentation techniques such as k-means clustering, Gaussian mixture model segmentation and fuzzy c-means are applied to the pre-processed MR images. The image segmentation results are evaluated using several performance measures, such as precision, recall, Tanimoto coefficient and Dice similarity index in reference to ground truth images. The highest average Dice coefficient is achieved by k-means (0.189) before post-processing and GMM (0.208) after post-processing. Unsupervised clustering-based brain tumour segmentation based on just image pixel intensity in single-spectral brain MRI without adaptive post-processing algorithm cannot achieve efficient and robust segmentation results

The computation of some properties of additive and multiplicative groups of integers modulo n using C++ programming

This research is focused on two types of finite abelian groups which are the group of integers under addition modulo , and the group of integers under multiplication modulo , where is any positive integer at most 200. The computations of some properties of the group including the order of the group, the order and inverse of each element, the cyclic subgroups, the generators of the group, and the lattice diagrams get more complicated and time consuming as n increases. Therefore, a special program is needed in the computation of these properties. Thus in this research, a program has been developed by using Microsoft Visual C++ Programming. This program enables the user to enter any positive integer at most 200 to generate answers for the properties of the groups

Placement and routing in VLSI design problem using single row routing technique

Two major problems are involved in VLSI design, namely, the placement of components and routing between these components. Single row routing problem is a combinatorial optimization problem of signi¯cant importance for the design of com- plex VLSI multi layer printed circuit boards (PCB's). The design involves conductor routing that makes all the necessary wiring and interconnections between the PCB modules, such as pins, vias, and backplanes. In very large systems, the number of interconnections may exceed tens of thousands. Therefore, we have to optimize the wire routing and interconnections and thus determine the e±cient designs. Kernighan- Lin algorithm, traveling salesman problem, simulated annealing algorithm and single row routing problem are used to ¯nd the best design. Included here are some simple examples to ¯nd the results. A simulation program using Microsoft Visual C++ is developed to simulate the single row routing problem using the simulated annealing algorithm