SEQUENCING PROBLEMS.

Slides:



Advertisements
Similar presentations
Your performance improvement partner 2/25/
Advertisements

The following 5 questions are about VOLTAGE DIVIDERS. You have 20 seconds for each question What is the voltage at the point X ? A9v B5v C0v D10v Question.
Operations Scheduling
Session II – Sequencing
Sequencing algorithms for multiple machines
ECE 667 Synthesis and Verification of Digital Circuits
Lesson 08 Linear Programming
Production and Operations Management Systems
Linear Programming Problem
Chapter 3: Planning and Scheduling Lesson Plan
Scheduling.
Scheduling.
1 9. S EQUENCING C ONSTRUCTION T ASKS Objective: To understand the problem of sequencing tasks in a manufacturing system, and the methods of finding optimal.
Operation Research Chapter 3 Simplex Method.
Math443/543 Mathematical Modeling and Optimization
Linear Programming Applications
Scheduling.
Sequencing Problem.
1 Chapter 15 Scheduling. 2 Scheduling: Establishing the timing of the use of equipment, facilities and human activities in an organization Answering “when”
CHAPTER 19 Scheduling Operations Management, Eighth Edition, by William J. Stevenson Copyright © 2005 by The McGraw-Hill Companies, Inc. All rights reserved.
1© 2003 by Prentice Hall, Inc. Upper Saddle River, NJ The Wyndor Glass Company Problem (Hillier and Liberman) The Wyndor Glass Company is planning.
LINEAR PROGRAMMING SIMPLEX METHOD.
Scheduling.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. 16 Scheduling.
CHP-4 QUEUE.
15-1Scheduling William J. Stevenson Operations Management 8 th edition.
Transportation Transportation models deals with the transportation of a product manufactured at different plants or factories supply origins) to a number.
Chapter 7 Transportation, Assignment & Transshipment Problems
15-1Scheduling William J. Stevenson Operations Management 8 th edition.
1 1 Slide Short – Term Scheduling Professor Ahmadi.
GROUP MEMBERS AMARASENA R.G.C. (061004D) DE MEL W.R. (061013E) DOLAPIHILLA I.N.K. (061017U) KUMARAJITH R.M.E. (061031G)
Scheduling Process and Production Management.
1 Short Term Scheduling. 2  Planning horizon is short  Multiple unique jobs (tasks) with varying processing times and due dates  Multiple unique jobs.
1 Operation Scheduling- II The Multi-Machine Case Look! There are two machines.
CSE 589 Part VI. Reading Skiena, Sections 5.5 and 6.8 CLR, chapter 37.
Scheduling. Scheduling: The allocation of resources over time to accomplish specific tasks. Demand scheduling: A type of scheduling whereby customers.
1 Network Models Transportation Problem (TP) Distributing any commodity from any group of supply centers, called sources, to any group of receiving.
Operational Research & ManagementOperations Scheduling Economic Lot Scheduling 1.Summary Machine Scheduling 2.ELSP (one item, multiple items) 3.Arbitrary.
Parallel Machine Scheduling
Session 10 University of Southern California ISE514 September 24, 2015 Geza P. Bottlik Page 1 Outline Questions? Comments? Quiz Introduction to scheduling.
LIMITATIONS OF ALGORITHM POWER
© The McGraw-Hill Companies, Inc., Chapter 12 On-Line Algorithms.
Prof. Yuan-Shyi Peter Chiu
Transportation Problems Joko Waluyo, Ir., MT., PhD Dept. of Mechanical and Industrial Engineering.
11 -1 Chapter 12 On-Line Algorithms On-Line Algorithms On-line algorithms are used to solve on-line problems. The disk scheduling problem The requests.
Waiting Line Theroy BY, PRAYASH NEUPANE, KARAN CHAND & SANTOSH SHERESTHA.
QUANTITATIVE METHODS FOR MANAGERS ASSIGNMENT MODEL.
Product A Product B Product C A1A1 A2A2 A3A3 B1B1 B2B2 B3B3 B4B4 C1C1 C3C3 C4C4 Turret lathes Vertical mills Center lathes Drills From “Fundamentals of.
Planning and Scheduling.  A job can be made up of a number of smaller tasks that can be completed by a number of different “processors.”  The processors.
Critical Paths and Scheduling Tasks Circuits, Paths, and Schedules.
1 Job Shop Scheduling. 2 Job shop environment: m machines, n jobs objective function Each job follows a predetermined route Routes are not necessarily.
Exhaustive search Exhaustive search is simply a brute- force approach to combinatorial problems. It suggests generating each and every element of the problem.
deterministic operations research
Greedy Technique.
CHAPTER 8 Operations Scheduling
Comparing Three or More Means
Shop Scheduling Problem
FACILITY LAYOUT Facility layout means:
The basics of scheduling
Unit 4: Dynamic Programming
Chap 11 Learning Objectives
Scheduling Scheduling is an important tool for manufacturing and service industries, where it can have a major impact on the productivity of a process.
8 Job Sequencing & Operations Scheduling CHAPTER Arranged by
3. Brute Force Selection sort Brute-Force string matching
CSE (c) S. Tanimoto, 2001 Search-Introduction
Planning and Scheduling
3. Brute Force Selection sort Brute-Force string matching
Sequencing Sequencing: Determine the order in which jobs at a work center will be processed. Workstation: An area where one person works, usually with.
Chapter 1. Formulations.
3. Brute Force Selection sort Brute-Force string matching
Presentation transcript:

SEQUENCING PROBLEMS

Sequencing A problem in which it is necessary to determine the orders or sequences of jobs in which they should be performed so as to minimize the total effectiveness on the sum of the pertinent costs is known as sequencing problems.

A Sequencing problem could involve: Jobs in a manufacturing plant Aircraft waiting for landing and clearance Maintenance scheduling in a factory Programs to be run on a computer Customers in a bank.

TERMS USED: JOBS – Jobs/items/customers are the primary stimulus for sequencing. Number of Machines – a machine is characterized by a certain processing capability or facilities through which a job must pass before it is completed in job. Processing Time – It means the time each job requires at each machine. Total Elapsed Time – It is the time between starting the first job and completing the last one.

Idle Time – Processing It is the time the machine remains idle during the total elapsed time. Technological Order – It refers to the order in which various machines are required for completing the jobs. It is also known as Processing order. No Passing Rule – It implies that passing is not allowed i.e. the same order of the jobs is maintained over each machine. If each of n- jobs are to be processed on 2 machines A & B in the order AB then this rule will mean that each job will go to A first and then to B.

JOB ARRIVAL PATTERN Categories of Job Arrival Pattern:- Job Arrival Pattern can be defined as the pattern in which a job arrives and joins the system. The arrival pattern may be fixed and known, variable but known and variable & unknown. Categories of Job Arrival Pattern:- Static Arrival Pattern – If all jobs arrive simultaneously. Dynamic Arrival Pattern – Where the jobs arrive continuously.

ASSUMPTIONS No machine can process more than one job at a time. The processing times on different machines are independent of the order in which they are processed. The time involved in moving a job from one machine to another is negligibly small. Each job once started on a machine is to be performed upto completion on that machine. All machines are of different types. All jobs are completely known and are ready for processing. A job is processed as soon as possible but only in the order specified.

Types of Sequencing Problems Problems with ‘n’ jobs through one machine. Problems with ‘n’ jobs through two machines. Problems with ‘n’ jobs through three machines. Problems with ‘n’ jobs through ‘m’ machines. Problems with ‘n’ jobs through one machine (dependent set up time) (as Assignment ). Problems with two jobs through ‘m’ machines.

Problems with ‘n’ jobs through one machine Methods Shortest Processing Time (SPT) Rule Weighted Scheduling Processing Time (WSPT) Rule

Problems with ‘n’ jobs through 2 machines Methods Heuristic Method Combinatorial Method

Heuristic Method Suggested by S.M.Johnson & Bellman. Procedure is as follows: - Select the smallest processing time occurring in the list Ai or Bj, if there is a tie select either of the smallest processing time. If the smallest time is on machine A, then place it at first place if it is for the B machine place the corresponding job at the last place. Cross off that job. If there is a tie for minimum time on both the machines then select machine A first and machine B last and if there is tie for minimum on machine A (same machine) then select any one of these jobs first and if there is tie for minimum on machine B then select any of these jobs in the last.

Repeat step 2 & 3 to the reduced set of processing times obtained by deleting the processing time for both the machines corresponding to the jobs already assigned. Continue the process placing the job next to the first or next to the last and so on till all jobs have been places and it is called optimum sequence. After finding the optimum sequence we can find the following: Total Elapsed Time = Total time between starting the first job of the optimum sequence on machine A and completing the last job on machine B. Idle time on machine A. Idle time on machine B.

Combinatorial Method This method has three stages: Compare operation time on machine A (ta) with machine B (tb). Give the code (Aa) 1 if ta > tb and code - 1 if ta < tb. Determine the minimum of the two operating time Ba, where Ba = min(ta, tb). Give comparatic weightage of different jobs f(a), where f(a) = Aa/Ba. the optimal sequence for the job is determined by arranging the jobs in ascending order of their weights f(a). Assumption – the jobs have no priority i.e. no job is preferred to other job and storage space is available for all the jobs.

Problems with ‘n’ jobs on 3 machines Machine A Machine B Machine C 1 2 3 4 . i n A1 A2 A3 A4 Ai An B1 B2 B3 B4 Bi Bn C1 C2 C3 C4 Ci Cn

There is no general solution at present however previous method given by Johnson can be applied if the following two conditions are satisfied: Condition 1 – Min Ai ≥ Max Bi and/ or Condition 2 – Min Ci ≥ Max Bi Method: Replace given problem into 2 fictitious machines G & H where, Gi=Ai+Bi, Hi=Bi+Ci, and so on Now apply same procedure and find out optimal sequence.

Problems with ‘n’ jobs through ‘m’ machines Job/Machines A B C…. M 1 2 3 4 5 A1 A2 A3 A4 A5 B1 B2 B3 B4 B5 C1…. C2…. C3…. C4….. C5…. M1 M2 M3 M4 M5 n An Bn Cn…. Mn

There is no solution available at present, however if any of the following conditions are met , we can proceed further: Condition 1 – Min A ≥ Max B,C,M-1 and/ or Condition 2 – Min M ≥ Max B,C,M-1 Method: Replace given problem into 2 fictitious machines G & H where, Gi=Ai+Bi+Ci+(M-1), Hi=Bi+Ci+(M-1)+M, and so on Now apply same procedure and find out optimal sequence. Alternatively convert the given problem into a no. of 2 machine sub problems.

Problems with ‘n’ jobs through one machine (dependent set up time) These problems can be solved as the Assignment Problems using special case of Travelling Salesman.

Problems with 2 jobs through ‘m’ machines Graphical method is used for such type of problems. The steps are given below: Construct a two – dimensional graph where the X – axis represent the processing time and sequence of job 1 and the M1 machine; whereas, Y – axis represents the processing tome and sequence of job 2 on M2 machine. It may be noted that scale used must be same for both the machines. Shade the area where machine would be occupied by the two jobs at the same time. The processing of both jobs can be represented by a continuous path which consists of horizontal, vertical and 45 degree diagonal segment.

The path starts at the lower left corner and stops at the upper right corner, while avoiding the shaded area in the graph. In other words, the path is not allowed to pass through shaded areas which correspond to operating both jobs concurrently on the same machine. Any horizontal movement will indicate the progress of job 1 whereas job 2 is idle. Any vertical movement will reveal that the job 2 is in progress while job 1 is idle. Minimum elapsed time for any job is the processing time of the job + Idle time of the same job.