{"id":57568,"date":"2023-09-02T15:17:53","date_gmt":"2023-09-02T15:17:53","guid":{"rendered":"https:\/\/www.inspirenignite.com\/anna-university\/cie352-design-and-analysis-of-algorithms-syllabus-for-industrial-2021-regulation-professional-elective-iv\/"},"modified":"2023-09-02T15:17:53","modified_gmt":"2023-09-02T15:17:53","slug":"cie352-design-and-analysis-of-algorithms-syllabus-for-industrial-2021-regulation-professional-elective-iv","status":"publish","type":"post","link":"https:\/\/www.inspirenignite.com\/anna-university\/cie352-design-and-analysis-of-algorithms-syllabus-for-industrial-2021-regulation-professional-elective-iv\/","title":{"rendered":"CIE352: Design and Analysis of Algorithms syllabus for Industrial 2021 regulation (Professional Elective-IV)"},"content":{"rendered":"

Design and Analysis of Algorithms detailed syllabus for Industrial Engineering (Industrial) for 2021 regulation curriculum has been taken from the Anna Universities<\/a> official website and presented for the Industrial students. For course code, course name, number of credits for a course and other scheme related information, do visit full semester subjects post given below. <\/p>\n

For Industrial Engineering 5th Sem scheme and its subjects, do visit Industrial 5th Sem 2021 regulation scheme<\/a>. For Professional Elective-IV scheme and its subjects refer to Industrial Professional Elective-IV syllabus scheme<\/a>. The detailed syllabus of design and analysis of algorithms is as follows. <\/p>\n

Course Objectives:<\/h4>\n

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Unit I<\/h4>\n

ANALYSING ALGORITHMS\t9<\/strong>
\nThe Role of Algorithms in Computing – Growth of Functions – Recurrences – The Substitution Method – The Recurrence Tree Method – The Master Method – Probabilistic Analysis and Randomized Algorithms – Amortized Analysis – Aggregate Analysis – Accounting Method\n<\/p>\n

Unit II<\/h4>\n

DIVIDE AND CONQUER & GREEDY DESIGN STRATEGIES\t9<\/strong>
\nAnalysis of Quick Sort, Merge Sort – Quick Sort Randomized Version – Sorting in Linear Time – Lower Bounds for Sorting – Selection in Expected Linear Time – Selection in Worst case Linear Time – Greedy Algorithms – Elements of Greedy Strategy – Huffman Code, Dijkstra\u2019s Shortest Path Algorithm.\n<\/p>\n

Unit III<\/h4>\n

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Unit IV<\/h4>\n

FLOW NETWORKS AND STRING MATCHING\t9<\/strong>
\nFlow Networks – Ford Fulkerson Method – String Matching – Naive String Matching Algorithm – Knuth Morris Pratt Algorithm – Analysis.\n<\/p>\n

Unit V<\/h4>\n

NP PROBLEMS\t9<\/strong>
\nNP-Completeness – Polynomial Time Verification – Theory of Reducibility – Circuit Satisfiability – NP – Completeness Proofs – NP Complete Problems: Vertex Cover, Hamiltonian Cycle and Traveling Salesman Problems – Approximation Algorithms -Approximation Algorithms to Vertex – Cover and Traveling Salesman Problems.\n<\/p>\n

Course Outcomes:<\/h4>\n