MIT Subject Listing & Schedule
Fall 2024 Search Results

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4 subjects found.

15.726 Pricing

()
Prereq: None
Units: 1-0-2
Credit cannot also be received for 15.818

Focuses on practical pricing tactics. Presents a framework for the steps firms should take when thinking about pricing a new product or improving the pricing performance of an old product. Tools covered include monadic pricing surveys, empirical price elasticity calculations, and conjoint. Restricted to Executive MBA and Sloan Fellow MBA students.
Staff

15.818 Pricing

(); first half of term
Prereq: 15.809, 15.814, or permission of instructor
Units: 3-0-3
Credit cannot also be received for 15.726
You must participate in Sloan's Course Bidding to take this subject.
Ends Oct 18. Lecture: MW10-11.30 (E51-149) or MW1-2.30 (E51-149) or MW2.30-4 (E51-149)

Framework for understanding pricing strategies and analytics, with emphasis on entrepreneurial pricing. Topics include economic value analysis, elasticities, customization, complementary products, pricing in platform markets, and anticipating competitive responses.
C. Tucker
No textbook information available

16.888[J] Multidisciplinary Design Optimization

()
(Same subject as EM.428[J], IDS.338[J])
Prereq: 18.085 or permission of instructor
Units: 3-1-8

Systems modeling for design and optimization. Selection of design variables, objective functions and constraints. Overview of principles, methods and tools in multidisciplinary design optimization (MDO). Subsystem identification, development and interface design. Design of experiments (DOE). Review of linear (LP) and non-linear (NLP) constrained optimization formulations. Scalar versus vector optimization problems. Karush-Kuhn-Tucker (KKT) conditions of optimality, Lagrange multipliers, adjoints, gradient search methods, sensitivity analysis, geometric programming, simulated annealing, genetic algorithms and particle swarm optimization. Constraint satisfaction problems and isoperformance. Non-dominance and Pareto frontiers. Surrogate models and multifidelity optimization strategies. System design for value. Students execute a term project in small teams related to their area of interest. 
O. de Weck

EM.428[J] Multidisciplinary Design Optimization

()
(Same subject as 16.888[J], IDS.338[J])
Prereq: 18.085 or permission of instructor
Units: 3-1-8

Systems modeling for design and optimization. Selection of design variables, objective functions and constraints. Overview of principles, methods and tools in multidisciplinary design optimization (MDO). Subsystem identification, development and interface design. Design of experiments (DOE). Review of linear (LP) and non-linear (NLP) constrained optimization formulations. Scalar versus vector optimization problems. Karush-Kuhn-Tucker (KKT) conditions of optimality, Lagrange multipliers, adjoints, gradient search methods, sensitivity analysis, geometric programming, simulated annealing, genetic algorithms and particle swarm optimization. Constraint satisfaction problems and isoperformance. Non-dominance and Pareto frontiers. Surrogate models and multifidelity optimization strategies. System design for value. Students execute a term project in small teams related to their area of interest. 
O. de Weck