functionalities included in each sprint, which makes the planning problem difficult. In this paper we formalize the planning problem and propose an optimization model that, given the estimates made by the project team and a set of development constraints, produces an optimal sprint plan that maximizes the business value perceived by users. The planning problem is converted into a multi-knapsack problem with constraints, given a linear programming formulation, and solved using the IBM ILOG CPLEX Optimizer
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Automation is the use of control systems and information technologies to reduce the need for human work in the production of goods and services. In the scope of industrialization, automation is a step beyond mechanization. Whereas mechanization provided human operators with machinery to assist them with the muscular requirements of work, automation greatly decreases the need for human sensory and mental requirements as well. Automation plays an increasingly important role in the world economy and
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Refuelling Schedule for Airports By Kiran R K Jitha Babu Shyam S Sreeraj S CHAPTER 1 INTRODUCTION 1.1 REFUELLING Refuelling is an important aspect with respect to the airports since it determines the ground time of an aero
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Received in revised form 12 March 2012 Accepted 12 March 2012 Keywords: Carbon footprint Reverse logistics Greenhouse emissions Case study a b s t r a c t Due to the environmental legislation and regulations, manufacturing firms have realized the importance of adopting environmental friendly supply chain management (SCM) practices. In this paper, a mixed integer linear model is developed for a carbon footprint based reverse logistics network design. The proposed model aims at minimizing climate
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Hazarika INDIAN INSTITUTE OF MANAGEMENT, KOZHIKODE COMPUTATIONAL COMPLEXITY Computational Complexity is a measure of the computational time taken by a particular algorithm. In a scenario where there are multiple algorithms available for a particular problem, the effectiveness of any particular algorithm is gauged on the basis of the time constraint. This is done by breaking the algorithm into its basic steps and then taking a count of each of them. Hence greater is the number of steps, greater is the
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2. Interprocess Communication, Distributed Objects and Remote Invocation: Introduction , External data representation and marshalling, Communication models, Communication between distributed objects , Remote procedure call Case study: Interprocess communication in UNIX, Java RMI . (4.1-4.6, 5.1-5.5 of Text1) ..6hrs 3. Operating System Introduction , Operating system layer, Processes and
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030 Faculty: Dr. Kais Zaman North South University Table of Contents Objectives 3 Brief Company Profile 4 Methodologies 5 Need for the forecasting 5 Forecasting Methods 8 Qualitative Analysis 10 Linear Programming 13 Conclusion 17 Objectives The primary objective is to find the demand and supply management techniques and the tools that the company uses to predict the demand for their products. The project will also
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present in this paper a new, complete method for distributed constraint optimization, based on dynamic programming. It is a utility propagation method, inspired by the sum-product algorithm, which is correct only for tree-shaped constraint networks. In this paper, we show how to extend that algorithm to arbitrary topologies using a pseudotree arrangement of the problem graph. Our algorithm requires a linear number of messages, whose maximal size depends on the induced width along the particular pseudotree
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polynomial and radical equations, linear functions and their graphs, systems of linear equations, functions and their properties and triangles and trigonometric functions. Activities will include solving problems and using appropriate technological tools. Prerequisite: GE184 Problem Solving or TB184 Problem Solving or GE150 Survey of the Sciences or equivalent; Prerequisite or Corequisite: TB133 Strategies for the Technical Professional or equivalent GE184 Problem Solving | A 4 credit hour Science
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Abbreviated version of this report is published as "Trends in Computer Science Research" Apirak Hoonlor, Boleslaw K. Szymanski and M. Zaki, Communications of the ACM, 56(10), Oct. 2013, pp.74-83 An Evolution of Computer Science Research∗ Apirak Hoonlor, Boleslaw K. Szymanski, Mohammed J. Zaki, and James Thompson Abstract Over the past two decades, Computer Science (CS) has continued to grow as a research field. There are several studies that examine trends and emerging topics in CS research
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