Common due date assignment and single-machine scheduling with release times to minimize the weighted number of tardy jobs

2016 ◽  
Vol 33 (1) ◽  
pp. 239-249 ◽  
Author(s):  
Chuanli Zhao
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Due Date ◽  
Due Date Assignment ◽  
Common Due Date ◽  
Release Times ◽  
Number Of Tardy Jobs ◽  
Weighted Number ◽  
Tardy Jobs

Single Machine Scheduling and due Date Assignment with Past-Sequence-Dependent Delivery Times and General Position-Dependent Processing Times

2014 ◽  
Vol 624 ◽  
pp. 675-680
Author(s):  
Yu Fang Zhao
Keyword(s):  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Scheduling Problems ◽  
Due Date ◽  
Due Date Assignment ◽  
Processing Times ◽  
Delivery Times ◽  
Weighted Number ◽  
Tardy Jobs

We studied single machine scheduling problems in which the jobs need to be delivered to customers after processing. It is assumed that the delivery times are proportional to the length of the already processed jobs, and a job's processing time depended on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs and the cost of due date assignment. We analyzed these problems with two different due date assignment methods and conclude that the problems are polynomial time solvable.

The Parallel Machine Scheduling with Considering the Due Date Assignment, Earliness, Weighted Number of Tardy Jobs and Batch Delivery

2021 ◽  
pp. 1-20
Author(s):  
M. B. Fakhrzad ◽  
Saber Shamsadini ◽  
Abbasali Jafari-Nodoushan
Keyword(s):  
Objective Function ◽  
Machine Scheduling ◽  
Parallel Machine Scheduling ◽  
Parallel Machine ◽  
Due Date ◽  
Due Date Assignment ◽  
Number Of Tardy Jobs ◽  
Weighted Number ◽  
Vehicle Capacity ◽  
Tardy Jobs

In this paper, parallel machine scheduling problem is considered under due date assignment, earliness, weighted number of tardy jobs, facilities costs and shipping products by limited vehicle capacity. The orders of the customer are presented with a due date. Each order is scheduled and assigned to one of the machines according to due date, delay weight and penalty of increasing of due date and shipped in the batch. The problem is known as NP-hardness, therefore a Genetic Algorithm (GA) is proposed to solve the problem. The results are also compared with the CPLEX solver in the GAMS. Finally, sensitivity analysis for the problem parameters is performed in relation to the objective function. The results showed a direct relationship between objective function with the weighted tardiness and processing time, also an inverse relationship with the number of machines and vehicle capacity.

Single Machine Scheduling and Due Date Assignment with Past-Sequence-Dependent Delivery Times and Position-Dependent Processing Times

2014 ◽  
Vol 1006-1007 ◽  
pp. 498-503 ◽  
Author(s):  
Yu Fang Zhao
Keyword(s):  
Single Machine ◽  
Dynamic Programming Algorithm ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Programming Algorithm ◽  
Due Date ◽  
Due Date Assignment ◽  
Processing Times ◽  
Delivery Times ◽  
Tardy Jobs

This paper considers single machine scheduling and due date assignment problems in which the jobs need to be delivered to customers after processing. It is assumed that the delivery times are proportional to the length of the already processed jobs, and a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs and the cost of due date assignment. We analyze the problems with two different due date assignment methods and conclude that the problems are polynomial time solvable. We provide a dynamic programming algorithm with O(n3) times for the problems.

New Properties for Solving the Single-Machine Scheduling Problem with Early/Tardy Jobs

2017 ◽  
Vol 26 (3) ◽  
pp. 531-543
Author(s):  
Hemmak Allaoua ◽  
Bouderah Brahim
Keyword(s):  
Genetic Algorithm ◽  
Single Machine ◽  
Machine Scheduling ◽  
Single Machine Scheduling ◽  
Computational Effort ◽  
Due Date ◽  
Common Due Date ◽  
Mathematical Properties ◽  
Penalty Costs ◽  
Tardy Jobs

AbstractThis paper presents a mathematically enhanced genetic algorithm (MEGA) using the mathematical properties of the single-machine scheduling of multiple jobs with a common due date. The objective of the problem is to minimize the sum of earliness and tardiness penalty costs in order to encourage the completion time of each job as close as possible to the common due date. The importance of the problem is derived from its NP-hardness and its ideal modeling of just-in-time concept. This philosophy becomes very significant in modern manufacturing and service systems, where policy makers emphasize that a job should be completed as close as possible to its due date. That is to avoid inventory costs and loss of customer’s goodwill. Five mathematical properties are identified and integrated into a genetic algorithm search process to avoid premature convergence, reduce computational effort, and produce high-quality solutions. The computational results demonstrate the significant impact of the introduced properties on the efficiency and effectiveness of MEGA and its competitiveness to state-of-the-art approaches.

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