PPT-Towards a Fast Heuristic for MINLP

John W Chinneck M Shafique Systems and Computer Engineering Carleton University Ottawa Canada Introduction Goal Find a good quality integerfeasible MINLP solution quickly Trade off accuracy for speed. This anchoringand adjustment heuristic is assumed to underlie many intuitive judgments and insuf64257cient adjustment is commonly in voked to explain judgmental biases However despite extensive research on anchoring effects evidence for adjustmentba Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. Feedback: Tutorial 1. Describing a state.. Entire state space vs. incremental development.. Elimination of children.. Closed and the solution path.. Generation of children – effects on search.. Heuristic Search. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. CPSC 481: HCI I. Fall 2014. 1. Anthony Tang with acknowledgements to Saul Greenberg and Ehud . Sharlin. Learning Objectives. By the end of this class, you should be able to:. » understand and describe . unknown environment. Athanasios Ch. Kapoutsis. , Christina M. . Malliou. , Savvas A. Chatzichristofis and Elias B. . Kosmatopoulos. School of Electrical and Computer Engineering,. Democritus University of Thrace, Xanthi, Greece. Rhea . McCaslin. The GDS Network. Guarded Discrete Stochastic – neural network developed by Johnston and . Adorf. 2. Hubble Space Telescope. Scheduling Problem. PROBLEM: Between 10,000 – 30,000 astronomical observations per year . Continued. Before we continue. Breadth-First. Depth-First. Uniform Cost. Iterative-Deepening. Before we continue. Breadth-First. S,A,B,D,C,G. Depth-First. S,A,C,D,B,G. Uniform Cost. S,A,B,D,C,G. Iterative-Deepening. Continued. Before We Start. HW1 extended to Monday. Submit online (now working) and bring paper print out. Questions?. Competency Demo next Wednesday. Study Guide Posted. We will have some discussion time on Monday. Rhea . McCaslin. The GDS Network. Guarded Discrete Stochastic – neural network developed by Johnston and . Adorf. 2. Hubble Space Telescope. Scheduling Problem. PROBLEM: Between 10,000 – 30,000 astronomical observations per year . 10. . Tutorial. 1. Today’s Activity: Heuristic Evaluation. General steps:. Perform an independent assessment of which heuristics a system violates. With a small group of 4, discuss and aggregate your individual results, listed by heuristic. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. heuristic search methods are known as “weak methods” because of their generality and because they do not apply a great deal of knowledge .