The focus area of this paper is on the assignment problem with budget constraints which is one of the application area of combinatorial optimization that operates on the domain of those optimization problems,in which the set of feasible solutions is discrete or can be reduced to discrete,and in which the goal is to find the best solution. It is particularly concerned with solving the unconstrained assignment problems with Hungarian algorithm and the constrained assignment problem by cutting plane or outer linearization algorithm for solving the Lagrangian dual problem in which, at each iteration,the function that approximates the dual function is optimized. The paper is divided in to two chapters. In the first chapter,the classical assignment problem,the problem of finding optimum (minimum or maximum) cost or profit assignment a set of workers or resources to jobs or activities to gather with its mathematical formulation,solution methods and special cases in assignment problems were considered. Under the second chapter, we have considered generalization of the classical assignment problem concerning resource(or budget) constraints, due to the variety of real life problems.
In this book we consider the Frequency Assignment Problem, where the objective is to minimize the cost due to interference arising in a solution. We use a quadratic 0-1 integer programming formulation of the problem as a basis to derive new lower bounds and problem reduction rules. A tree search algorithm that uses the lower bounds and dominance criteria is also presented. Computational results are shown on standard benchmark instances from the literature.
Assignment Problem is one of the first fundamental problems in the area of combinatorial optimization. Despite its historical roots, the problem has tremendous importance to date, due to its numerous real life applications in like facility location, personnel scheduling, job scheduling, production planning, project assignment, task assignment, time-tabling, vehicle routing, storage space allocation, etc. This book comprises some real life assignment and related problems involving imprecise cost/time parameters. In order to represent those imprecise parameters, interval numbers have been used here as this representation is the best among others. The associated problems have been solved using Genetic Algorithm efficiently. A salient feature of this book is that most of the algorithms have been written in a lucid manner with suitable examples using figures. This book should interest academicians, OR/GA practitioners and executives of different industries and business organizations.
The problem of distributing goods from depots to consumers plays an important role in the management of many distribution systems, and therefore when it is programmed efficiently it may yield significant savings. In a typical distribution system, trucks provide pick-up and delivery services to customers that are geographically dispersed in a given area. In many of its applications, the main objective of distribution is to find a set of routes for such trucks, satisfying a variety of constraints, so as to minimize the total distribution cost. This work focuses on a decision model for a real world problem. The problem reveals itself as assignment of trucks to routes by Latex Foam Rubber Products Limited-Kumasi, Ghana. This study addresses the problem of finding an efficient assignment of the limited number of trucks at the company’s disposal to the routes they ply while serving its customers outside the metropolis. In this work we use a solution procedure based on Munkres Assignment Algorithm for optimal assignment of non-homogenous fleet of trucks to a given set of routes, where Latex Foam Rubber Products Limited-Kumasi, distributes its products to its customers.
This book explains the port operations and proposes approaches that aim to improve the most important successive steps in container terminal management activities. A multi-period assignment problem that seeks to allocate vessels to berthing spaces and quay cranes is proposed to handle the quayside operations. Subsequently, on the yard side, a discrete-event simulation model for the real life detailed processes performed during the handling of import containers is developed. In particular, the model focuses on the storage assignment problem at the operational level in a container terminal with a multiple-berth structure. An approach by means of a hierarchical structure is adapted to partition the assignment problem into two sub-problems and solve each of them using separate decision rules. Suggested storage policies are evaluated in view of the overall performance of the container terminal.
In recent years, we have witnessed a tremendous growth of communication networks. This is because they are widely used in all walks of life, and this trend continues increasing. The research on computer communication networking field has also grown explosively due to a large variety of combinatorial optimisation problems. One of these problems is the Terminal Assignment Problem which implies fixing the minimum cost links to construct a network between a specified set of terminals and concentrators. A good solution for this problem should maintain small distances between concentrators and terminals assigned to them without exceeding the capacity of any concentrator. Additionally, it should also maintain a balanced distribution of terminals among concentrators. The intractability of this problem is a motivation for the pursuits of different approximation algorithms. In this book, we explore several metaheuristics applied to the Terminal Assignment Problem and other similar problems. Simulation results verify the effectiveness of these algorithms.
This book concentrates on the problem of credit assignment. The goal of this work is to propose ensemble classification method, which can be applied to solve credit decisions problems. The method uses switching class labels techniques to construct complex classification system, which solves two of typical data mining problems observed in financial data mining field: the problem of imbalanced data and the problem of asymmetric cost matrix. The performance of the proposed solution is going to be evaluated on German Credits dataset.
The Weapon-Target Assignment (WTA) problem is one of the most important problems of military applications of operations research. In this paper, hybrid Nested Partitions (NP) method is proposed to solve WTA problems. The proposed algorithm is named as “Hybrid NP method with intelligent greedy search”. This proposed algorithm combines the advantages of the NP method and intelligent greedy search and shows great efficiency for solving the WTA problem.
Routing and Wavelength Assignment (RWA) is a well known problem in Wavelength Division Multiplexing (WDM) networks. RWA problem is reported in the literature as a single objective ILP problem. In this article, we formulated the RWA problem as a multi objective ILP problem. An attempt is made to obtain a feasible solution using genetic algorithm (GA). The parameters considered for optimization are congestion among the individual lightpath requests, connection set up time, the number of intermediate hops traversed and the number of fibers used to honor the established connection requests. We considered ARPANET and NSFNET for our simulation.
This book contains basic concepts and various methods available to solve different types of problems in Operations Research like Linear Programming Problem, Transportation Problem, Assignment Problem etc. Methods are demonstrated through good number of examples for easy understanding and helps for self study. List of Reference books from which the data is collected given at the end of the book to facilitate the readers for more information and for theoretical concepts.
Mesh Wireless Local Area Network (WLAN) is a promising access network to enhance channels utilization, extend access coverage using simple and cheap network components. Power management affects mesh WLAN network coverage, topology, throughput, traffic routing and end to end delay. Channel assignment affects the mesh nodes interference level and so the transmission capacity. It also controls the number of nodes share the same channel which increases the probability of collision and reduces the network throughput. In this book, the power management problem is formulated to show its impact on mesh WLAN network throughput. Then this formulation is used to propose a new ranking based cooperative game strategy. Mesh WLAN channel assignment problem is also formulated. Then different algorithms throughput and processing delay is analyzed. This analysis is based on evaluating average users’ data rate and processing delay for different assignment techniques in many mesh WLAN network configurations.
In this book several multilayer particle deposition models are studied using simulations and analytical calculations. Multilayer particle deposition models are an extension of the classic car parking problem, first studied by the Hungarian mathematician Renyi. Several interesting properties of these type of processes are revealed. The focus of the book lies on the non-equality of end-densities of the layers. In some models the end-densities are lower in higher layers whereas in other models the end-densities are higher in higher layers. It is shown that in the latter case this is a result of self-organization. As an application, the results are used to analyze the so-called sequential frequency assignment process. For this purpose, the assignment of radio frequencies by national telecom authorities (using the foremost priority procedure) is regarded as a two-dimensional multilayer deposition model with discs.
Scheduling problems occur in all economic domains from computer engineering to manufacturing techniques. These problems are generally defined as decision making problems with the aim of optimizing one or more scheduling criteria. Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical job shop scheduling problem which allows an operation to be processed by any machine from a given set. It is more complex than job shop scheduling problem, because of the additional need to determine the assignment of operations to machines. FJSSP is very important in both fields of production management and combinatorial optimization. Owing to the high computational complexity, it is quite difficult to achieve an optimal solution with the traditional techniques. In this connection, suitable algorithms (or) techniques are required to solve the FJSSP. This book provides wide knowledge in the metaheuristics with scheduling field.
A wireless mesh networks (WMNs) has emerged recently, WMN consist of two types of nodes mesh routers and mesh clients.WMN is dynamically self-organized and self-configured, with the nodes in the network automatically establishing and maintaining mesh connectivity among themselves. Channel assignment is a critical issue in WMN which is the mapping between the available channels and the radios at each node such that the network performance is optimized, and hence the focus of this work along with static channel assignment, multi-radio, multi-channel. Multi-radio MAC can potentially achieve higher network capacity than single-radio MAC. We design and implement a new agent (DSBCA) distributed channel assignment spanner base, the routing protocol Optimize the network performance considering the throughput, end-to-end delay, connectivity and the interference of our channel assignment algorithm. Base on the network simulations NS2.34 on Linux Fedora and our proposed channel assignment algorithm improved the throughput, minimal-connectivity preserving channel assignment algorithm.
Ring networks are suited to deliver a large amount of bandwidth in a reliable and inexpensive way. An optimal load balancing is of paramount importance because it increases the system capacity and improves the overall ring performance. In this context an important optimization problem is the Weighted Ring Loading Problem. That is the design of a direct path for each request, in a communication network, in a way that high load on the arcs/edges will be avoided, where an arc is an edge endowed with a direction. We study two variants of this problem without demand splitting. The work presented in this document is also focused in other two problems that arise in the design of optical telecommunication networks, namely the Synchronous optical network Ring Assignment Problem (SRAP) and the Intraring synchronous optical network Design Problem (IDP). In SRAP, the objective is to minimize the number of rings and in IDP, the objective is to minimize the number of Add-Drop Multiplexers. Both problems are subject to a ring capacity constraint. To solve these four NP-hard problems, are proposed several metaheuristic algorithms including bio-inspired randomized search heuristics.
"This book is an excellent read for transit agencies who care to operate transit services for best revenue generation practices." - M Ehsanul Bari (Bobby), MS, Department of Civil Engineering Texas A&M University. "The most significant part of the book is the simulation work and smart use of heuristics in the solving the feeder transit problem." -Rahul Jain, MS, Department of Industrial Engineering, Texas A&M University. "A good insight into how transportation systems can impact community livability by following the principles and recommendations laid down in the book." - Sanjeev Rai Bhatia, Physiotherapist. "The results highlighted in the work is surely going to change the way public transportation have been functioning." -Arvind Singh Negi, B Tech, IIT Delhi (currently a renowned Civil Engineering Consultant). "The mathematical touch to the nearest street assignment problem is excellent". -J Rakesh, B Tech, IIT Delhi.
The Evil Within: The Assignment – это первое из двух дополнение к The Evil Within, главной героиней которого является Джулия Кидман, напарница детектива Себастьяна Кастелланоса. В этом дополнении игроки получат часть ответов на те вопросы, которые у них остались после финала оригинальной игры.
Queueing theory is an essential concept to review in light of tactical wireless communications and networks. Wireless communication systems, in particular frequency spectrum, are expensive and it is imparative that we make optimal use of frequency spectrum. Therefore the performance analysis is an important factor in the designing phase of the networks. This book addresses the performance evaluation and enhancement of wireless networks, examining the channel assignment problem of cellular networks.
The thesis focuses on student written plagiarism as a research problem. From prior research on plagiarism and scientific knowledge three hypotheses are developed: intentional plagiarism as an easy way to perform an assignment, unintentional plagiarism caused by misleading flow of digital texts, unawareness of instructions, and lack of feedback, and different identity of students, as opposed to scholars.
The fundamental goal of multi-agent robotics is simple: how to create control laws and behaviors that, when executed by each individual robot, some desirable global behavior emerges. The global behavior may range from something as simple as the robots meeting at a single point, to something as complex as a collective search and rescue mission. Our research focuses on one of the more fundamental issues in multi-agent, mobile robotics: the formation control problem. The idea is to create controllers that cause robots to move into a predened formation shape. This is a well studied problem for the scenario in which the robots know in advance to which point in the formation they are assigned. In our case, we assume this information is not given in advance, but must be determined dynamically. This thesis presents an algorithm that can be used by a network of mobile robots to simultaneously determine ecient robot assignments and formation pose for rotationally and translationally invariant formations. This allows simultaneous role assignment and formation sysnthesis without the need for additional control laws.
The efficient management of Change Requests (CRs) is fundamental for successful software maintenance; however the assignment of CRs to developers is an expensive aspect in this regard, due to the time and expertise demanded. To overcome this, researchers have proposed automated approaches for CR assignment. Although these proposals present advances to this topic, they do not consider many factors inherent to the assignments, such as: developers’ workload, CRs severity, interpersonal relationships, and developers know-how. Actually, as we demonstrate in this work, CR assignment is a complex activity and automated approaches cannot rely on simplistic solutions. Ideally, it is necessary to consider and reason over contextual information in order to provide an effective automation. Beyond investigating all these aspects through an extensive systematic literature review, this work also proposes a context-aware architecture solution to semi-automated assignment of CRs.
Revision with unchanged content. This study investigated the influence of computer-generated reminders on the rate in which distance learners submitted assignments and completed courses. The computer-generated reminders, sent via email, served as a time management support strategy. Participants were randomly divided into two groups: control and treatment. Both groups received a list of target due dates for course assignments. The control group did not receive reminders. The treatment group received reminders when they failed to submit an assignment by a target due date. The results indicated no significant difference between the control and treatment groups in terms of assignment submission rates and course completion rates. However, results of this study did reveal that the number of assignments in a distance course influences the timeliness of assignment completion and the likelihood of course completion.
Modern day public transport assignment faces lots of problems. Solutions may exist but needs some form of backings. A sensitivity analysis in most cases could just be sufficient to provide this backing. The developments in this book are very important for students, academic researchers and policy makers. The book provides an extensive review on transit assignment, sensitivity analysis and OmniTRANS. It highlights important conclusions such as:- - Passenger access-egress distances significantly affects their access stop choices. - The travel distance parameter of the generalized cost function has the highest influence on transit assignment - The number of transfers to be made by passengers significantly determines their generalized cost of travel - A carefully conducted partial sensitivity analysis can provide better predictions than a Monte-Carlo sensitivity analysis. As a policy advice to public transport operators in Flanders-Belgium, the developments in this book suggest that; to improve transit assignment, it is sufficient to reduce passengers access-egress distances & the number of transfers either through the institution of more direct transit lines or missing links.
Most practical systems and control problems are pure multi-objective problems. Multi-objective or vector-objective optimization problem is characterized by the partial ordering of its solution space. This, unlike in single objective optimization problem, leads to the notion of non-inferiority and the Pareto-optimal solution set. As it has been observed that the vector-optimization problem translates to a scalar optimization problem if a functional that completely orders the solution space can be found. A very important question in the transformation of the vector optimization problem into a scalar optimization problem-form that needs to be answered is that of the equivalence of the scalar problem and the original vector problem. The book proposed a scalarization function which is a sum of squares of the objective functionals. This reduces the vector optimization problem to a quadratic distance problem or the intersection ellipsoid of minimum volume with the trade-off surface. This method has been applied to pure and robust multi-objective Linear Quadratic Regulator (LQR) problem, and to mixed-norm multi-objective problem.
This study investigated the problem solving processes and behaviours exhibited by Grade 6 pupils during the process of problem solving in mathematics. The data were gathered through the use of an observation checklist on which problem solving processes and behaviours shown by participants were immediately recorded. Twenty five pupils of mixed ability of Tafira Primary School in their second term in 1999 made up the sample for this study. These participants were observed and the data coded on observation checklists. The data were analysed qualitatively using the descriptive mode. The results highlighted that during the process of problem solving, children employed problem solving processes and exhibited behaviours consistent with problem solving in small cooperative groups in the learning of mathematics. The results also show that the use of problem solving processes by learners is a result of practice and experience in actual problem solving. The awarding of scores in problem solving for moving a step towards problem resolution or complete resolution is motivational on the part of the learners.
Transportation problem is one of the important areas in operation research, which is widely used to make a decision in engineering, business, management and many other fields. In the field of operation research, Network Analysis plays an important role to optimization. In this thesis “A study of Transportation Problem (TP) & Network Analysis with TORA applications”, we consider the transportation problem which is a linear programming problem having particular significance in optimization theory. We study some new initial and optimal solution method with some established methods and we comparing the solution. We also study some network problem to optimize the result. Finally software TORA has been used to show the variations in the methods of solving Transportation Problem (TP) & Network Problem. By using TORA, the solution can be found in short time.
The book is intended for the researchers in Operations Research, Network, Economics and Management Science. This book contained the basic concepts of transportation Problem and the solution methodology. The main feature of this book is developed the similar concepts and methodology for Cost Varying Transportation Problem(CVTP). The Capacitated Transportation Problem under Vehicles can be solved easily by help of CVTP. Numerous problems are given either as worked at examples or as exercise. The main silent features of this book are that the researchers have the scope to extent the work in Multi-objective Transportation Problems, Multi-objective Capacitated Transportation Problem, Interval Transportation Problem, Multi-stage Transportation Problem, etc. We hope, this book lights on new researchers.
For the last decades, Transport Demand and Mobility has been a continuously developing branch in the transport literature. This is reflected in the great amount of papers published on scientific magazines trying to solve the traffic assignment and trip matrix estimation problems. This fact shows the difficulty to elaborate an effective model able to reproduce the real behaviour. These models use several data inputs (prior trip matrix, link counts, etc.), only from a subset of the problem variables, and its size will depend on the available budget. One problem of these models is the high number of possible solutions which is usually solved by finding one where the model results and the real data match up. Nevertheless a model does not have to reproduce only the real data, but also all the variables. Therefore the problem must consist of reproducing the reality in a precise form with minimum cost. The aim of this work consists of proposing new models, which allow us to update the traffic flow predictions from a small subset of real data. To this end, a Gaussian Bayesian Network is used, and so, probability intervals are obtained to get an idea of the associated uncertainties.
View selection is important in many data-intensive systems e.g., commercial database and data warehousing systems to improve query performance. The view selection problem is one of the most complex problem solving: a NP-hard problem. In a distributed environment, the problem becomes more challenging. Indeed, it includes another issue which is to decide on which computer nodes the selected views should be materialized. The principal objective of this manuscript is to provide a novel and efficient approach to address the view selection problem. For this purpose, we designed a solution using constraint programming which is known to be efficient for the resolution of NP-hard problems and a powerful method for modeling and solving combinatorial optimization problems. Constraint programming is a general framework which relies on a combination of techniques that deal with reasoning. To solve a given problem by means of constraint programming, the problem must be represented as a constraint satisfaction problem. This part of the problem solving is called modeling. Then, the resolution of the modeled problem is performed automatically by the constraint solver in the solving stage.
The highly competitive environment in today's wireless and cellular network industries is making the management of systems seek for better and more advance techniques to keep masses of data, complexity of systems and deadline constrains under control with a lower cost and higher efficiency. Therefore, the management is getting significant attentions by researchers in order to increase the efficiency of the resource usage to provide high quality services. Two of the cornerstones of the management system in wireless and cellular network are carrier assignment and packet scheduling. Therefore, this work focuses on analysis and development of carrier assignment and packet scheduling methods in multi-band Wi-Fi and LTE-A networks.