Presentation is loading. Please wait.

Presentation is loading. Please wait.

© J. Christopher Beck 20051 Lecture 6: Job Shop Scheduling Introduction.

Similar presentations


Presentation on theme: "© J. Christopher Beck 20051 Lecture 6: Job Shop Scheduling Introduction."— Presentation transcript:

1 © J. Christopher Beck Lecture 6: Job Shop Scheduling Introduction

2 © J. Christopher Beck Outline Job Shop Scheduling LEKIN Basic Definition Introduction to Solution Techniques

3 © J. Christopher Beck Job Shop Scheduling Job Operation/Task/ Activity Precedence Constraint

4 © J. Christopher Beck Job Shop Scheduling makespan JSP is Hard RCPSP is a generalization of JSP

5 © J. Christopher Beck Your Very Own JSP Can you find a schedule with a makespan of 31? Don’t forget about the precedence constraints on the activities in each job Activities Jobs1234 1M1, 9M2, 8M3, 4M4, 4 2M1, 5M2, 6M4, 3M3, 6 3M3, 10M1, 8M2, 9M4, 2

6 © J. Christopher Beck Solving the JSP Many, many approaches 20,300 hits on Google Scholar Also used to solve other scheduling problems and other optimization problems We are going to spend the next 6 lectures talking about them

7 © J. Christopher Beck Dispatch Rules Whenever a machine is free, look at all operations that can be scheduled and pick on with a simple rule: SPT: shortest processing time LPT: longest processing time EDD: earliest due date Try out SPT Activities Jobs1234 1M1, 9M2, 8M3, 4M4, 4 2M1, 5M2, 6M4, 3M3, 6 3M3, 10M1, 8M2, 9M4, 2

8 © J. Christopher Beck Shifting Bottleneck Pick most loaded resource Find optimal one-machine schedule Pick next most loaded resource Find optimal one-machine schedule consistent with previous one-machine schedules (This is a bit simplified)

9 © J. Christopher Beck Tabu Search Start with a random schedule Make a “move” (e.g., swap two operations) Remember you last few moves and don’t undo them Keep going until you get bored

10 © J. Christopher Beck Integer Programming and Branch-&-Bound Represent problem as an IP Sequence of every pair of operations is a 0-1 variable Use Branch-&-Bound (B&B) to find solution Will find optimal solution (if given enough time)

11 © J. Christopher Beck Constraint Programming B&B (but not IP) plus inference Every time you branch, use specialized algorithms to find other decisions that must be true May also use sophisticated branching heuristics Also will find optimal given time

12 © J. Christopher Beck Summary Dispatch Rules Shifting Bottleneck Tabu Search Integer Programming Constraint Programming Heuristic & incomplete: No guarantees But: work well for large problems Will find optimal (if given enough time)

13 © J. Christopher Beck LEKIN Demo


Download ppt "© J. Christopher Beck 20051 Lecture 6: Job Shop Scheduling Introduction."

Similar presentations


Ads by Google