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Efficient Algorithms and Optimization Techniques for Problem Solving

Learn about algorithms, data structures, and optimization to efficiently solve common problems. Course materials cover complexity analysis, abstract data types, sorting, searching, and more.

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Efficient Algorithms and Optimization Techniques for Problem Solving

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  1. TTIT33 – TemaAlgorithms and OptimizationOrganization issues Jan Maluszynski, IDA, 2006 http://www.ida.liu.se/~TTIT33 janma @ ida.liu.se Subject: TTIT33 Jan Maluszynski - HT 2006

  2. Course Goals Efficient solving of optimization problems • Algorithms • Basics of algorithms analysis (complexity) • Abstract Data Types : abstract formulation of commonly used data-processing operations • Data structures: commonly used techniques of representing data in computer memory • Standard solutions for commonly used problems: sorting, searching, selection • Optimization • Combinatorial optimization problems • Their complexity analysis • Classification of such problems and efficient algorithms for their solution Jan Maluszynski - HT 2006

  3. Staff • Jan Maluszynski IDA: • Course leader • Lectures in Algorithms • Kaj Holmberg MAI: • Lectures in Optimization • Labs in Optimization • Fredrik Kuivinen IDA: • Labs in Algorithms /Java • Eva Törnqvist TEMA: • Evaluation of presentation technique at the oral exam • Simin Nadjm-Tehrani IDA: • Terminansvarig • Anne Moe IDA • Course secretary Jan Maluszynski - HT 2006

  4. The components • Algorithms • 7 Lectures • 1 Lab IDA; register inWebReg this week • Optimization • 14 Sessions including lectures and problem solving • 2 Labs MAI • Own studies: 202 hours ! • Base groups • Scenarios (Vinjetter) • Integration Lab: Data Structures in Optimization techniques, solved in base groups Jan Maluszynski - HT 2006

  5. Exams • Written exam • problems on algorithms and on optimization • allowed material: the books at home page • Oral exam • An optimization problem distributed in advance • An algorithm is to be developed (pseudocode) • Individual oral presentation of the solution to 3 teachers; 15 min + discussion Register today for December or January Jan Maluszynski - HT 2006

  6. Scenarios/Vinjetter Published at the homepage • describe situations for using techniques taught in this course • are to be used for discussions in base groups • Scenario 3 is the base for the Integration Lab addressing both algorithms and optimization. Jan Maluszynski - HT 2006

  7. Selected Literature • Algorithms • Goodrich, Tamassia: Data Structures and Algorithms in Java (4th edition), 2005 • Cormen et al.: Introduction to Algorithms (2nd edition), 2001 • Lewis, Denenberg: Data Structures & Their Algorithms, 1991(out of print) • On-line collection of problems and solutions (TDDB57) linked at home page • Optimization • Kaj Holmberg: Kombinatorisk optimiering med linjärprogrammering (kompendium 2005) Jan Maluszynski - HT 2006

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