This paper considers scheduling n jobs on a single machine where the job processing times anddue dates are independent random variables with arbitrary distribution functions.We consider the casethat the weighted job t...This paper considers scheduling n jobs on a single machine where the job processing times anddue dates are independent random variables with arbitrary distribution functions.We consider the casethat the weighted job tardiness in expectation is minimized.It is assumed that job's due dates arecompatible with processing times and weights.We show that the jobs should be sequenced indecreasing stochastic order of their due dates.展开更多
In this paper, a single-machine scheduling model with a given common due date and simple linear processing times was considered. The objective is the total weighted tardiness penalty and earliness award. Some polynomi...In this paper, a single-machine scheduling model with a given common due date and simple linear processing times was considered. The objective is the total weighted tardiness penalty and earliness award. Some polynomial time solvable cases for this problem are given. A dynamic programming algorithm was provided and a branch and bound algorithm for general case of the problem was provided based on a rapid method for estimating the lower bound.展开更多
This paper investigates the common due-window assignment scheduling problem with deteriorating jobs on a single machine in which the processing time of a job is a proportional function of its starting time.The goal is...This paper investigates the common due-window assignment scheduling problem with deteriorating jobs on a single machine in which the processing time of a job is a proportional function of its starting time.The goal is to minimize the maximum value of earliness and tardiness penalties,as well as due-window location cost,and size cost.Depending on whether the location and size of due-window are known,this paper studies three relevant cases,all of which are solvable in polynomial time.展开更多
The single machine scheduling problem which involves uncertain job due dates is one of the most important issues in the real make-to-order environment. To deal with the uncertainty, this paper establishes a robust opt...The single machine scheduling problem which involves uncertain job due dates is one of the most important issues in the real make-to-order environment. To deal with the uncertainty, this paper establishes a robust optimization model by minimizing the maximum tardiness in the worst case scenario over all jobs. Unlike the traditional stochastic programming model which requires exact distributions, our model only needs the information of due date intervals. The worst case scenario for a given sequence that belongs to a set containing only n scenarios is proved, where n is the number of jobs. Then, the model is simplified and reformulated as an equivalent mixed 0-1 integer linear programming(MILP) problem. To solve the MILP problems efficiently, a heuristic approach is proposed based on a robust dominance rule. The experimental results show that the proposed method has the advantages of robustness and high calculating efficiency, and it is feasible for large-scale problems.展开更多
In this paper, a single-machine scheduling model with a given common due date is considered. Job processing time is a linear decreasing function of its starting time. The objective function is to minimize the total we...In this paper, a single-machine scheduling model with a given common due date is considered. Job processing time is a linear decreasing function of its starting time. The objective function is to minimize the total weighted earliness award and tardiness penalty. Our aim is to find an optimal schedule so as to minimize the objective function. As the problem is NP-hard, some properties and polynomial time solvable cases of this problem are given. A dynamic programming algorithm for the general case of the problem is provided.展开更多
The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been inves...The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching rule as the initial solution for SA, and the three superior dispatching rules as part of the initial population for GA. Moreover, improved versions of SA and GA are proposed using an insertion algorithm. Extensive computational experiments reveal that the improved versions of SA and GA perform about 95% better than SA and GA. The improved version of GA outperforms the improved version of SA by about 3.5%.展开更多
This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation...This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.展开更多
The strong non-deterministic polynomial-hard( NP-hard)character of job shop scheduling problem( JSSP) has been acknowledged widely and it becomes stronger when attaches the nowait constraint,which widely exists in man...The strong non-deterministic polynomial-hard( NP-hard)character of job shop scheduling problem( JSSP) has been acknowledged widely and it becomes stronger when attaches the nowait constraint,which widely exists in many production processes,such as chemistry process, metallurgical process. However,compared with the massive research on traditional job shop problem,little attention has been paid on the no-wait constraint.Therefore,in this paper, we have dealt with this problem by decomposing it into two sub-problems, the timetabling and sequencing problems,in traditional frame work. A new efficient combined non-order timetabling method,coordinated with objective of total tardiness,is proposed for the timetabling problems. As for the sequencing one,we have presented a modified complete local search with memory combined by crossover operator and distance counting. The entire algorithm was tested on well-known benchmark problems and compared with several existing algorithms.Computational experiments showed that our proposed algorithm performed both effectively and efficiently.展开更多
文摘This paper considers scheduling n jobs on a single machine where the job processing times anddue dates are independent random variables with arbitrary distribution functions.We consider the casethat the weighted job tardiness in expectation is minimized.It is assumed that job's due dates arecompatible with processing times and weights.We show that the jobs should be sequenced indecreasing stochastic order of their due dates.
基金supported by the National Natural Science Foundation of China (Grant No.19771057)
文摘In this paper, a single-machine scheduling model with a given common due date and simple linear processing times was considered. The objective is the total weighted tardiness penalty and earliness award. Some polynomial time solvable cases for this problem are given. A dynamic programming algorithm was provided and a branch and bound algorithm for general case of the problem was provided based on a rapid method for estimating the lower bound.
基金supported by LiaoNing Revitalization Talents Program(No.XLYC2002017).
文摘This paper investigates the common due-window assignment scheduling problem with deteriorating jobs on a single machine in which the processing time of a job is a proportional function of its starting time.The goal is to minimize the maximum value of earliness and tardiness penalties,as well as due-window location cost,and size cost.Depending on whether the location and size of due-window are known,this paper studies three relevant cases,all of which are solvable in polynomial time.
基金supported by the National Natural Science Foundation of China(61503211,U1660202)。
文摘The single machine scheduling problem which involves uncertain job due dates is one of the most important issues in the real make-to-order environment. To deal with the uncertainty, this paper establishes a robust optimization model by minimizing the maximum tardiness in the worst case scenario over all jobs. Unlike the traditional stochastic programming model which requires exact distributions, our model only needs the information of due date intervals. The worst case scenario for a given sequence that belongs to a set containing only n scenarios is proved, where n is the number of jobs. Then, the model is simplified and reformulated as an equivalent mixed 0-1 integer linear programming(MILP) problem. To solve the MILP problems efficiently, a heuristic approach is proposed based on a robust dominance rule. The experimental results show that the proposed method has the advantages of robustness and high calculating efficiency, and it is feasible for large-scale problems.
文摘In this paper, a single-machine scheduling model with a given common due date is considered. Job processing time is a linear decreasing function of its starting time. The objective function is to minimize the total weighted earliness award and tardiness penalty. Our aim is to find an optimal schedule so as to minimize the objective function. As the problem is NP-hard, some properties and polynomial time solvable cases of this problem are given. A dynamic programming algorithm for the general case of the problem is provided.
文摘The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching rule as the initial solution for SA, and the three superior dispatching rules as part of the initial population for GA. Moreover, improved versions of SA and GA are proposed using an insertion algorithm. Extensive computational experiments reveal that the improved versions of SA and GA perform about 95% better than SA and GA. The improved version of GA outperforms the improved version of SA by about 3.5%.
文摘This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.
基金National Natural Science Foundations of China(Nos.61174040,61104178)Shanghai Commission of Science and Technology,China(No.12JC1403400)the Fundamental Research Funds for the Central Universities,China
文摘The strong non-deterministic polynomial-hard( NP-hard)character of job shop scheduling problem( JSSP) has been acknowledged widely and it becomes stronger when attaches the nowait constraint,which widely exists in many production processes,such as chemistry process, metallurgical process. However,compared with the massive research on traditional job shop problem,little attention has been paid on the no-wait constraint.Therefore,in this paper, we have dealt with this problem by decomposing it into two sub-problems, the timetabling and sequencing problems,in traditional frame work. A new efficient combined non-order timetabling method,coordinated with objective of total tardiness,is proposed for the timetabling problems. As for the sequencing one,we have presented a modified complete local search with memory combined by crossover operator and distance counting. The entire algorithm was tested on well-known benchmark problems and compared with several existing algorithms.Computational experiments showed that our proposed algorithm performed both effectively and efficiently.
