Advanced Optimization using AMPL Workshop

Program Objective

Optimization technologies have become key tools in making important business decisions that increase competitive advantage. Optimization, through the use of mathematical models and software techniques, is used to assist organisations with solving their complex business problems in areas such as manufacturing, distribution, finance and scheduling. The success of optimization projects depends on many different factors such as which modelling tools are used, integration with corporate data and the selection of the most efficient solution algorithms available for the problem.

Program Benefits

At the end of the workshop, the participants will be able to develop their own optimization models, link them to data sources and solve the models using state-of-the-art commercial solvers. Participants will also acquire a good knowledge on how to embed optimization models into applications.

By attending this workshop you will be able to:

  • Build your own optimization applications.
  • Identify the best use of optimization techniques and how to deploy them for your purposes.
  • Gain an insightful and realistic view on the use of optimization for business applications.
  • Prepare and consolidate data from disparate sources for optimization applications.
  • Identify solving and fine-tuning requirements in your optimization applications.

Who should attend

  • Project Managers
  • System Architects
  • Operations Research consultants
  • Business Analyst
  • OR Model Developers
  • Integration and test engineers

Workshop Agenda

Day 1

  • Introduction and Overview
  • Introduction to LP Terminology, model representation and mathematical models

An Introduction to Modelling via AMPLDev

  • Participants will learn how to use various functionalities of AMPL Studio
  • An Introduction to AMPL Syntax

  • A formal presentation of basic AMPL modelling constructs
  • Efficient/Structured Modelling

  • A process to create an efficient model starting from the problem that is presented
  • Goal programming/Elastic Constraints

  • Presentation of an introductory financial model that includes goal programming
  • Using EXCEL as data source for AMPL

  • How to connect an AMPL model to Excel
  • Workshop (I) Financial Model

  • Participants investigate, formulate and solve an introductory financial model using AMPL
  • Hands-on models partial description: bond stripping, portfolio,ALM, supply chain

  • The models for the hands-on sessions will be described and hints for their implementation will be given
  • Hands-On Session

  • The attendees should form groups and implement one of the models presented in the previous session
  • Day 2

      Mixed Integer Programming Problems

    • Integer problems involving binary variables, semi-continuous variables and special ordered set variables are introduced. A few discrete programming problems are explained
    • Case study: IP with buying threshold

    • An IP model with semi-continuous variables is introduced
    • An Introduction to AMPL scripting functionalities

    • Introduction to AMPL's powerful scripting functionalities
    • Continuation of Hands-On Session

    • The groups should continue the implementation of the chosen models and prepare brief presentations of their results
    • Introducing AMPL API

    • How to embed optimisation models in applications
    • Part I: Heuristic for solving Integer Programs using AMPL Script

    • Different kind of heuristics to speed up solution of problems are proposed here and prototyped using AMPL scripting functionalities
    • Part II: AMPL API implementation of AMPL script procedures

    • Examples of integration of models and scripts into applications
    • Attendees' Presentations and feedback

    • The groups have ten minutes each to present the model they implemented and their results

    Day 3

      Stochastic Programming: optimum decision making under uncertainty: an overview

    • A theoretical background to decision making under uncertainty will be given, with a particular focus on Stochastic Programming.
    • Stochastic Programming and Risk Measures

      Introduction of a Stochastic Programming Model

      Hands-on: Expected Value, Wait and See and Deterministic Equivalent: an ALM model

    • Various models will be described and attendees will be helped with their implementation in AMPL.
    • Stochastic Extensions to AMPL: SAMPL

    • AMPL extensions to represent Stochastic Programming and Robust Optimisation problems, and problems with (Integrated) Chance Constraints.
    • SAMPL Example: an ALM model

    • An ALM model will be refined by the introduction of uncertainty and expressed using SAMPL syntax.
    • Solution Methods for Stochastic Programming

      Robust Optimisation

    Day 4

    Stochastic Programming and Scenario Generation: A modelling perspective

    • The role of scenario generation in SP will be illustrated
    • Scenario Generation: overview and desirable properties

      Hands-on: formulation of SP models in AMPL and SAMPL

    • The techniques and language features presented the day before will be applied to investigate an SP model
    • Hands-on: formulation of SP models in SAMPL

    • Chance Constraint and Integrated Chance Constraint formulation of some models in SAMPL
    • Investigation and simulation: Two-stage SP, ICCP and robust optimisation models

      Hands-on: formulation of SP models in SAMPL

    • Various SP models will be described and attendees will be helped in their implementation in SAMPL

    Ways to Train

    • Class Room
    • Virtual Class Room
    • On-Site Team Training

    Faculty details

    Professor Gautam Mitra

    Professor Gautam Mitra is an internationally renowned research scientist in the field of Operational Research in general and computational optimisation and modelling in particular. He has developed a world class research group in his area of specialisation with researchers from Europe, UK & USA. He has published three books and over hundred refereed research articles. He was Head of the Department of Mathematical Sciences, Brunel University between 1990 and 2001. In 2001 he has established CARISMA: The Centre for the Analysis of Risk and Optimisation Modelling Applications. CARISMA specialises in the research of Risk and Optimisation and their combined paradigm in decision modelling. Professor Mitra is a Director of OptiRisk Systems UK and OptiRisk India. Many of the research results of CARISMA are exploited through these companies.

    Dr. Cormac Lucas

    Dr. Cormac Lucas has extensive knowledge of Mathematical programming modelling, Pre-analysis and reduction techniques in linear programs and representation of logical expressions as MIPs. Dr Lucas has a PhD and BSc degree from Brunel University. He has held academic positions at CARISMA, Brunel University, London. Dr Lucas has published extensively in the area of optimisation modelling. He has led a number of industry projects on scheduling and decision support.

    Dr. Miguel Lejune

    Dr. Miguel Lejune is a tenured Associate Professor of Decision Sciences at the George Washington University (GWU). He is the recipient of the CAREER/Young Investigator Research Grant from the Army Research Office and of the IBM Smarter Planet Faculty Innovation Award. He was appointed (July 2013) committee member of the Stochastic Programming Society (COSP). Prior to joining GWU, he was a Visiting Assistant Professor in Operations Research at Carnegie Mellon University and worked as a Credit Risk Manager at FORTIS Bank.

    Miguel Lejeune’s areas of expertise/research interests include Stochastic Optimization, Probabilistic Programming, Financial Risk, Large-Scale and Applied Optimization, Supply Chain Management. He has published articles in Operations Research, Mathematical Programming, Interfaces, INFORMS Journal of Computing, Journal of Operations Management, European Journal of Operational Research, Quantitative Finance, Decision Analysis, Operations Research Letters, Journal of Optimization Theory and Applications, Networks, Annals of Operations Research, International Transactions of Operational Research, American Journal of Mathematical and Management Sciences, etc.

    Dr.Christian Valente

    Dr. Christian Valente joined OptiRisk in 2005 as software engineer, coming from the field of Artificial Intelligence. He has participated in the development and maintenance of many of the company’s products. Along with Dr Lucas he presents workshops and training sessions, and is the main technological advisor for external projects. He is the main designer and developer of SPInE, the OptiRisk modeling system for Stochastic Programming. He has completed his PhD in Mathematics at Brunel University, and his main research interests are Stochastic Programming and parallel computing. He has a first class degree in Computer Science from Politecnico di Milano, Milan, Italy and an MSc equivalent in Artificial Intelligence from the same institution. He speaks native Italian, fluent English and has a good understanding of German.

    Dr.Diana Roman

    Dr. Diana Roman has a PhD in Models for Choice under Risk, from the School of Information Systems, Computing and Mathematics, Brunel University, UK; MSc in Applied Statistics and Optimisation, and BSc in Mathematics, from University of Bucharest, Romania.

    Dr Roman is now a faculty member of CARISMA, a lecturer in the school of The School of Information Systems, Computing & Mathematics at Brunel University.

    Formerly she was a software developer at OptiRisk Systems (KTP associate in a partnership between OptiRisk systems and Brunel University), tasked with designing a software library of scenario generators to be integrated within the SPInE system.

    Her work experience comprises several years as a teaching assistant in the Department of Mathematics, Technical University of Civil Engineering, Bucharest. Her research interests include Risk decisions in finance (portfolio optimisation), financial risk measurement and modelling, scenario generation, stochastic programming. Dr Roman speaks Romanian and English.

    Dr Cristiano Arbex Valle

    Dr Cristiano Arbex Valle joined OptiRisk in 2011 as software engineer / researcher, coming from a background of Computer Science. He plays active roles in important company's products. He is currently responsible for the maintenance and development of Fortsp, OptiRisk (Integer) Stochastic Programming solver. He also plays a major role in the development and research of News Analytics related products. Dr. Valle obtained his PhD in Mathematics at Brunel University, where his main research interests were optimisation techniques and financial modelling. He also holds a position as Operations Research class teacher at London School of Economics. He has a degree in Computer Science from Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil, and an MSc in Operations Research from the same institution. Dr. Valle has been a software developer since 2003 where he worked for large Brazilian companies in the realm of aircraft maintenance and government financial control. He speaks native Portuguese, fluent English and has a good knowledge of Spanish.


    Date City Location
    21st- 24th September 2017 Chennai TBD


    Industry participants - Rs. 20,000 + taxes.

    Academic participants (Students/Teaching professionals) - Rs. 7,500 + taxes.

    10% early bird discount is offered, if registered before July 15th.

    10% group discount is offered, if registered as a group of three of more.

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    Sales Order Management

    Delivery Planning and Management

    Collection Management System

    12V DC Wireless Dot Matrix Printer

    Transportation Optimization

    Packing Optimization

    Production Planning and Scheduling

    Inventory Management

    Supply Chain Network Design

    Portfolio Optimization

    Engineering R&D


    Staff Augmentation

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