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I SY E 723

DYNAMIC PROGRAMMING AND ASSOCIATED TOPICS

3 credits.

General and special techniques of dynamic programming developed by means of examples. Shortest-path algorithms. Deterministic equipment replacement models. Resource allocation problem. Traveling-salesman problem. Knapsack problem. Analysis of inventory systems. General stochastic formulations. Markovian decision processes. Students are strongly encouraged to have knowledge of mathematical optimization (e.g., COMP SCI/I SY E/MATH/STAT 525 , I SY E 623 , COMP SCI/I SY E/MATH/STAT 726 ), knowledge of analysis (e.g., MATH/STAT 431 or 521 ) and programming ability (e.g., COMP SCI 200 or 301)

Prerequisites & course information

Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Identify basic components, such as the state space, of a dynamic program Audience: Graduate 2. Formulate and solve dynamic programs under different performance criteria such as finite horizon discounted reward/cost criteria Audience: Graduate 3. Apply dynamic programming tools and concepts in `traditional' industrial engineering applications such as supply chain, manufacturing, and healthcare Audience: Graduate Learning Outcomes: 1. Identify basic components, such as the state space, of a dynamic program Audience: Graduate 2. Formulate and solve dynamic programs under different performance criteria such as finite horizon discounted reward/cost criteria Audience: Graduate 3. Apply dynamic programming tools and concepts in `traditional' industrial engineering applications such as supply chain, manufacturing, and healthcare Audience: Graduate

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