Efficient Heuristics for Total Completion Time and Maximum Lateness Bicriteria Scheduling Problems

2020 ◽  
Vol 35 ◽  
pp. 110-121
Author(s):  
Saheed Akande
Keyword(s):  
Completion Time ◽  
Computational Experiment ◽  
Optimal Solution ◽  
Maximum Lateness ◽  
Total Completion Time ◽  
Release Dates ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Bicriteria Scheduling ◽  
Solution Methods

This paper considers the bicriteria scheduling problem of minimizing the total completion time and maximum lateness with zero release dates. The problem is NP hard, though Early Due Date (EDD) and Shortest Processing Time (SPT) rules yielded optimal solutions for maximum lateness and total completion time, respectively if each criterion were to be considered singly. Thus, the values of each of the criteria for the two proposed heuristics; SII and PI were compared to the optimal solution of the sub problems. Results of computational experiment on job sizes varies from 5-100 jobs showed that the two proposed solution methods yielded results not significantly different from the optimal. This is because the two heuristic yielded results not significantly from the optimal sub-problems for the two performance measures at 95% significant level.

New Solution Methods for Single Machine Bicriteria Scheduling Problems: Minimizing the Total Flowtime and Maximum Tardiness with Zero Release Dates

2018 ◽  
Vol 38 ◽  
pp. 144-153 ◽  
Author(s):  
Saheed Akande
Keyword(s):  
Single Machine ◽  
Computational Experiment ◽  
Optimal Solution ◽  
Release Dates ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Bicriteria Scheduling ◽  
Total Flowtime ◽  
Maximum Tardiness ◽  
Solution Methods

This paper considers the bicriteria scheduling problem of minimizing the maximum tardiness and total flowtime on single machine with zero release dates. The problem is NP hard, though Early Due Date (EDD) and Shortest Processing Time (SPT) rules yielded optimal solutions for maximum tardiness and total flowtime, respectively if each criterion were to be considered singly. Thus, the values of each of the criteria for the two proposed heuristics; AA and SA were compared to the optimal solution of the sub problems. Results of computational experiment on job sizes varies from 5-150 jobs showed that the SA heuristic is preferred over AA. This is because the heuristic SA yielded maximum tardiness and total flowtime not significantly different from the EDD and SPT results, respectively at 99% significant level. Though AA yielded optimal for total flowtime, the maximum tardiness results is significantly different from the EDD results.

A Generalized Algorithm for Solving Multicriteria Scheduling Problems

2011 ◽  
Vol 367 ◽  
pp. 653-666 ◽  
Author(s):  
Elkanah Oyetunji ◽  
Ayodeji E. Oluleye
Keyword(s):  
Completion Time ◽  
Scalar Function ◽  
The Other ◽  
Total Completion Time ◽  
Release Dates ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Multicriteria Scheduling ◽  
Time Criterion ◽  
Solution Methods

In this paper, the scheduling problem involving optimization of multiple criteria (or objectives) is explored. There are many variants of the problem. The particular variant, in which the objectives are aggregated into a scalar function (with each criterion having weight which denotes its relative importance), is considered. An algorithm which can be used to solve very large classes of the multicriteria scheduling problem is proposed. The proposed algorithm and two solution methods selected from the literature were evaluated on a total of 900 randomly generated multicriteria scheduling problems (ranging from 10 to 500 jobs). Two variants of the release dates (0 – 24 and 0 – 49) are utilized. Results show that the proposed algorithm performed better than the selected solution methods when the total completion time criterion is much more important than the other criteria. However, when the total completion time criterion is much less important than the other criteria, the selected solution methods outperformed the proposed algorithm. The results are consistent under the two variants of the release dates.

scholarly journals Realtime production scheduling and control systems in smart industry

Impact ◽  
2020 ◽  
Vol 2020 (8) ◽  
pp. 60-61
Author(s):  
Wei Weng
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Production Scheduling ◽  
Production Control ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Scheduling Problems ◽  
Smart Industry ◽  
And Control

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.

Theoretical Analysis on Powers-of-Two Applied to JSP

2011 ◽  
Vol 2 (2) ◽  
pp. 1-20
Author(s):  
V. Mahesh ◽  
L. Siva Rama Krishna ◽  
Sandeep Dulluri ◽  
C. S. P. Rao
Keyword(s):  
Job Shop ◽  
Job Shop Scheduling ◽  
Optimal Schedule ◽  
Optimal Solution ◽  
Mathematical Induction ◽  
Release Dates ◽  
Scheduling Problems ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Optimal Value

This paper discusses the scheduling of precedence-related jobs non-preemptively in a job shop environment with an objective of minimizing the makespan. Due to the NP-hard nature of the scheduling problems, it is usually difficult to find an exact optimal schedule and hence one should rely on finding a near to optimal solution. This paper proposes a computationally effective powers-of-two heuristic for solving job shop scheduling problem. The authors prove that the makespan obtained through powers-of-two release dates lies within 6% of the optimal value. The authors also prove the efficacy of powers-of-two approach through mathematical induction.

scholarly journals Minimizing Total Completion Time For Preemptive Scheduling With Release Dates And Deadline Constraints

2014 ◽  
Vol 39 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Cheng He ◽  
Hao Lin ◽  
Yixun Lin ◽  
Junmei Dou
Keyword(s):  
Completion Time ◽  
Total Completion Time ◽  
Release Dates ◽  
Preemptive Scheduling ◽  
Release Date ◽  
Enumeration Algorithm ◽  
Processing Times ◽  
Special Cases ◽  
Deadline Constraints ◽  
Special Case

Abstract It is known that the single machine preemptive scheduling problem of minimizing total completion time with release date and deadline constraints is NP- hard. Du and Leung solved some special cases by the generalized Baker's algorithm and the generalized Smith's algorithm in O(n2) time. In this paper we give an O(n2) algorithm for the special case where the processing times and deadlines are agreeable. Moreover, for the case where the processing times and deadlines are disagreeable, we present two properties which could enable us to reduce the range of the enumeration algorithm

scholarly journals A Single-Machine Two-Agent Scheduling Problem by a Branch-and-Bound and Three Simulated Annealing Algorithms

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shangchia Liu ◽  
Wen-Hsiang Wu ◽  
Chao-Chung Kang ◽  
Win-Chin Lin ◽  
Zhenmin Cheng
Keyword(s):  
Simulated Annealing ◽  
Branch And Bound ◽  
Single Machine ◽  
Completion Time ◽  
Optimal Solution ◽  
Total Completion Time ◽  
Practical Applications ◽  
Processing Resource ◽  
Agent Scheduling ◽  
Annealing Algorithms

In the field of distributed decision making, different agents share a common processing resource, and each agent wants to minimize a cost function depending on its jobs only. These issues arise in different application contexts, including real-time systems, integrated service networks, industrial districts, and telecommunication systems. Motivated by its importance on practical applications, we consider two-agent scheduling on a single machine where the objective is to minimize the total completion time of the jobs of the first agent with the restriction that an upper bound is allowed the total completion time of the jobs for the second agent. For solving the proposed problem, a branch-and-bound and three simulated annealing algorithms are developed for the optimal solution, respectively. In addition, the extensive computational experiments are also conducted to test the performance of the algorithms.

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