SIMULATION MODELING AND ANALYSIS

Name: SIMULATION MODELING AND ANALYSIS
Availability: OutOfStock

ISYE 620

과목 설명

Introduction to simulation modeling and analysis techniques with application to production, logistics, service, and other systems. Emphasis on model building, application of basic statistical data analysis, and the use of simulation for design, evaluation, and improvement of such systems. Introduction to available software. Case studies.

선수과목

(COMPSCI 200 , COMPSCI 220 , COMPSCI 300 , 301, 302, or placement into COMPSCI 300 ) and (STAT 224, STAT 312 , STAT 324 , or MATH/STAT 310 ), graduate/professional standing, or member of Engineering Guest Students

충족 요건

This course does not satisfy any prerequisites.

학점

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개설 시기

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평점

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변화 계산 불가

수료율

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변화 계산 불가

A 비율

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변화 계산 불가

학급 규모

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과거 데이터 대비 변화 없음

데이터 없음

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

SIMULATION AND PROBABILISTIC MODELING

ISYE 320

Analysis of stochastic systems using both analytic methods and computer simulation. Empirical and theoretical models of arrival and service processes. State spaces and state transition probabilities. Simulation of queuing and manufacturing systems. Continuous time Markov analysis of manufacturing systems. Simulation project management, testing and emerging trends.

SIMULATION MODELING LABORATORY

ISYE 321

Computer exercises involving generation and analysis of random variables, spreadsheet models of queuing systems, use of simulation software packages. Project.

LOGISTICS SYSTEMS DESIGN

ISYE 625

Practical methods for the planning, design and evaluation of complex logistics and distribution systems. Modeling techniques and solution approaches that reduce cumbersome details of logistics systems into models with a manageable number of parameters and decision variables. It shows how the solutions to these models are interpreted into optimal rules that guide the operation, design or planning process. Practical methods for the planning, design and evaluation of complex logistics and distribution systems. Modeling techniques and solution approaches that reduce cumbersome details of logistics systems into models with a manageable number of parameters and decision variables. It shows how the solutions to these models are interpreted into optimal rules that guide the operation, design or planning process. Builds on knowledge of introductory programming such as Python, Matlab, or R.

DESIGN AND ANALYSIS OF MANUFACTURING SYSTEMS

ISYE/ME 641

Covers a broad range of techniques and tools relevant to the design, analysis, development, implementation, operation and control of modern manufacturing systems. Case studies assignments using industry data will be used to elaborate the practical applications of the theoretical concepts.

STOCHASTIC MODELING TECHNIQUES

ISYE 624

Techniques for modeling systems in which uncertainty is an essential factor. Emphasizes why, how and when techniques can or cannot be applied, rather than their mathematical derivation. Case studies and/or examples from such areas as logistics, production, and service industries.