AWAS Automated Work Assignment System A Real World NP-Complete Problem Huy Truong – COT 6410 November 4, 2008.

Slides:



Advertisements
Similar presentations
What is Intractable? Some problems seem too hard to solve efficiently. Question 1: Does an efficient algorithm exist?  An O(a ) algorithm, where a > 1,
Advertisements

1 NP-Complete Problems. 2 We discuss some hard problems:  how hard? (computational complexity)  what makes them hard?  any solutions? Definitions 
NetWORKS Strategy Manugistics NetWORKS Strategy 6.2.
CSE332: Data Abstractions Lecture 27: A Few Words on NP Dan Grossman Spring 2010.
Example – calculating interest until the amount doubles using a for loop: will calculate up to 1000 years, if necessary if condition decides when to terminate.
NP-Complete Problems Reading Material: Chapter 10 Sections 1, 2, 3, and 4 only.
The Theory of NP-Completeness
NP-Complete Problems Problems in Computer Science are classified into
Integer Programming Integer programming is a solution method for many discrete optimization problems Programming = Planning in this context Origins go.
Analysis of Algorithms CS 477/677
Computational Complexity, Physical Mapping III + Perl CIS 667 March 4, 2004.
CSE 421 Algorithms Richard Anderson Lecture 27 NP Completeness.
Black-box (oracle) Feed me a weighted graph G and I will tell you the weight of the max-weight matching of G.
NP and NP- Completeness Bryan Pearsaul. Outline Decision and Optimization Problems Decision and Optimization Problems P and NP P and NP Polynomial-Time.
Linear Programming Applications
Hardness Results for Problems P: Class of “easy to solve” problems Absolute hardness results Relative hardness results –Reduction technique.
Halting Problem. Background - Halting Problem Common error: Program goes into an infinite loop. Wouldn’t it be nice to have a tool that would warn us.
Week 7 - Programming II Today – more features: – Loop control – Extending if/else – Nesting of loops Debugging tools Textbook chapter 7, pages
Scheduling Master - Slave Multiprocessor Systems Professor: Dr. G S Young Speaker:Darvesh Singh.
Automated Staff Scheduling Software Tim Curtois The OR Society Criminal Justice Special Interest Group 27 June 2012.
Terrence Hall Arizona State University CIS 440 September 11, 2012.
Complexity Classes Kang Yu 1. NP NP : nondeterministic polynomial time NP-complete : 1.In NP (can be verified in polynomial time) 2.Every problem in NP.
The Theory of NP-Completeness 1. What is NP-completeness? Consider the circuit satisfiability problem Difficult to answer the decision problem in polynomial.
This presentation is the property of Paradigm Information Systems It is confidential to the intended recipient for the purpose of evaluating FMS Any other.
WELCOME TO BP IU Scoops Session January 20, 2005.
TH EDITION Copyright © 2013, 2009, 2005 Pearson Education, Inc. 1 1 Equations and Inequalities Copyright © 2013, 2009, 2005 Pearson Education,
Nattee Niparnan. Easy & Hard Problem What is “difficulty” of problem? Difficult for computer scientist to derive algorithm for the problem? Difficult.
Complexity Classes (Ch. 34) The class P: class of problems that can be solved in time that is polynomial in the size of the input, n. if input size is.
Tonga Institute of Higher Education Design and Analysis of Algorithms IT 254 Lecture 8: Complexity Theory.
Lecture 22 More NPC problems
Great Theoretical Ideas in Computer Science.
MIT and James Orlin1 NP-completeness in 2005.
TECH Computer Science NP-Complete Problems Problems  Abstract Problems  Decision Problem, Optimal value, Optimal solution  Encodings  //Data Structure.
CSCI 2670 Introduction to Theory of Computing November 29, 2005.
RATIONAL EXPRESSIONS. Rational Expressions and Functions: Multiplying and Dividing Objectives –Simplifying Rational Expressions and Functions –Rational.
CSCI 3160 Design and Analysis of Algorithms Tutorial 10 Chengyu Lin.
Cliff Shaffer Computer Science Computational Complexity.
1 The Theory of NP-Completeness 2 Cook ’ s Theorem (1971) Prof. Cook Toronto U. Receiving Turing Award (1982) Discussing difficult problems: worst case.
Lecture 6 NP Class. P = ? NP = ? PSPACE They are central problems in computational complexity.
Instructor Neelima Gupta Table of Contents Class NP Class NPC Approximation Algorithms.
The Evolution of a Hard Graph Theory Problem – Secure Sets Ron Dutton Computer Science University of Central Florida 1.
NP-Complete Problems Algorithm : Design & Analysis [23]
Approximation Algorithms Department of Mathematics and Computer Science Drexel University.
1.1 Chapter 3: Proving NP-completeness Results Six Basic NP-Complete Problems Some Techniques for Proving NP-Completeness Some Suggested Exercises.
CS 3343: Analysis of Algorithms Lecture 25: P and NP Some slides courtesy of Carola Wenk.
CSE 589 Part V One of the symptoms of an approaching nervous breakdown is the belief that one’s work is terribly important. Bertrand Russell.
1 CS612 Algorithms for Electronic Design Automation CS 612 – Lecture 8 Lecture 8 Network Flow Based Modeling Mustafa Ozdal Computer Engineering Department,
CS6045: Advanced Algorithms NP Completeness. NP-Completeness Some problems are intractable: as they grow large, we are unable to solve them in reasonable.
1 Optimization Techniques Constrained Optimization by Linear Programming updated NTU SY-521-N SMU EMIS 5300/7300 Systems Analysis Methods Dr.
NP-completeness NP-complete problems. Homework Vertex Cover Instance. A graph G and an integer k. Question. Is there a vertex cover of cardinality k?
NP Completeness Piyush Kumar. Today Reductions Proving Lower Bounds revisited Decision and Optimization Problems SAT and 3-SAT P Vs NP Dealing with NP-Complete.
CSC 413/513: Intro to Algorithms
QUANTITATIVE METHODS FOR MANAGERS ASSIGNMENT MODEL.
SUBSET-SUM Instance: A set of numbers denoted S and a target number t.
1 P and NP. 2 Introduction The Traveling Salesperson problem and thousands of other problems are equally hard in the sense that if we had an efficient.
Algorithm Complexity By: Ashish Patel and Alex Golebiewski.
The NP class. NP-completeness Lecture2. The NP-class The NP class is a class that contains all the problems that can be decided by a Non-Deterministic.
Anytime, Anywhere Access Benefits Functionality Work Order Administration Dispatch Work Order Work Order Details New Work Order Additional Functionality.
Accounting Guru Cloud ERP (Enterprise Resource Planning) ERP Software https:
Together we can build something great FORWARD | 2016 FSM (Field Service Management) for contractERP Bill Natalie and Tracie Folscroft.
ICS 353: Design and Analysis of Algorithms NP-Complete Problems King Fahd University of Petroleum & Minerals Information & Computer Science Department.
More NP-Complete and NP-hard Problems
EMIS 8373: Integer Programming
The Simplex Method The geometric method of solving linear programming problems presented before. The graphical method is useful only for problems involving.
Approximation Algorithms
FACILITY LAYOUT Facility layout means:
ICS 353: Design and Analysis of Algorithms
The Simplex Method The geometric method of solving linear programming problems presented before. The graphical method is useful only for problems involving.
Copyright © 2017, 2013, 2009 Pearson Education, Inc.
Trevor Brown DC 2338, Office hour M3-4pm
Presentation transcript:

AWAS Automated Work Assignment System A Real World NP-Complete Problem Huy Truong – COT 6410 November 4, 2008

What is AWAS? AWAS is a workforce-management system developed by GTE Service Corporation (now Verizon) in the early 1990s. AWAS assigns jobs to field service technicians, allows technicians to report job status, completes work orders that flow directly into the billing system. AWAS is being used by two of the largest telecommunication corporations in North America: Verizon and Telus (Canada) I was a software developer on the AWAS program in 1998 at GTE Data Services in Tampa, FL

AWAS – High Level Architecture Customer Relationship Management (CRM) Automated Work Assignment System ( AWAS) Add Job Provide ETA Call Input Data Compute an Optimized Job Assignment People Management Software Available Technician, Skill Level Assign Jobs Provide Status Billing System Provide Billing Data Technician Performance Feedback Bill Customer

AWAS – An Optimization Problem Given:  Set of jobs with estimated labor hours, required skills, and location (customer location)  Number of available technicians with skills  Cost to travel between all customer locations Question:  What is the most cost effective way to assign jobs to technicians?

AWAS – Converted to a Decision Problem Given:  Set of jobs with estimated labor hours, required skills, and location (customer location)  Number of available technicians with skills  Cost to travel between all customer locations  Number of hours, k, that jobs must be completed Question:  Can we schedule jobs to technicians so that all jobs will be complete in k hours?

AWAS – Create A Math Model Given:  Set of pre-defined skills S = {s 1, s 2, s 3, … s n }  Set of locations L = {l 1, l 2, … l m }  Set of jobs J = {(s j, l j, hrs), (s k, l k, hrs)… (s v, l v, hrs)}  Set of technicians T = {(s i, s j, s m ), (s v, s k ), (s i )}  Set of travel cost C = {(l 1, l 2, cost), (l 1, l 3, cost)… (l m-1, l m, cost)}  A positive number k Question:  Can we schedule jobs, J, to technicians, T, so that all jobs will be complete in k hours?

AWAS – is a NP Problem 1.The AWAS problem is a decision problem 2.There is a yes instance verifier in polynomial time once the oracle provides the job assignments Therefore, AWAS decision problem is belong NP

AWAS – is a NP-Complete Problem Let’s consider the Multiprocessor Problem Given:  Set of tasks T = {t 1, t 2, … t n }  Set of processors P = {p 1, p 2, … p m }  And an positive integer t Question:  Can we schedule T so that all processors P will stop by some time t?

AWAS – is a NP-Complete Problem Let’s Create an instance of AWAS decision problem Given:  Set of pre-defined skills S = {s 1 } – one skill  Set of locations L = {l 1 } – one location  Set of jobs J = {(s 1, l 1, t1), (s 1, l 1, t 2 )… (s 1, l 1, t n )}  Set of technicians T = {(s 1 ), (s 1 ),… (s 1 )} – All technician has the same skill. Number of technician is equal to number of Processors  Set of travel cost C = {(l 1, l 1, 0)} – a single zero cost to travel from location 1 to location 1  A positive number k  t Question:  Can we schedule jobs, J, to technicians, T, so that all jobs will be complete in k hours?

AWAS - is a NP-Complete Problem Multiprocessor Scheduling is a restricted version of AWAS decision problem. Therefore, prove by restriction that:  All yes instances of AWAS decision problem would be yes instances of Multiprocessor Scheduling problem and vice versa Therefore, AWAS decision problem is a NP-Complete problem

AWAS - Interesting Facts AWAS also considers to assign the similar jobs to the same technician. This improves productivity since the technician works on the same problem all day AWAS handles jobs that need more than one technician AWAS reassigns jobs through out the day to react to cancellation & new jobs The original AWAS was written in C Verizon IT Solution promotes and sells AWAS to telecommunication companies around the Globe software-applications/workforce-management/awas- index.html

AWAS - Interesting Facts There are hate websites for AWAS since it “controls”, tracks, and maximizes field technicians productivities.  “Can you sit around and let this system control your lives, or are you going to stand up and fight against the new world order? Fear not, for we are here to protect you.” guide.html

AWAS - Questions