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
We consider a scheduling problem involving a single processor utilized by two customers with constant deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. Tradition...We consider a scheduling problem involving a single processor utilized by two customers with constant deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. Traditionally, such scenarios are modeled by assuming that each customer has the same criterion. In practice, this assumption may not hold. Instead of using a single criterion, we examine the implications of minimizing an aggregate scheduling objective function in which jobs belonging to different customers are evaluated with their individual criteria. We examine three basic scheduling criteria： minimizing makespan, minimizing maximum lateness, and minimizing total weighted completion time. We demonstrate all the scheduling problems considered are polynomially solvable.展开更多
Stochastic dynamic job shop scheduling pro- blem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatchin...Stochastic dynamic job shop scheduling pro- blem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 % and setup times less than processing times. Results indicate that shortest setup time （SIMSET） rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date （JMEDD） rule provides the best performance for make- span, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.展开更多
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.
文摘We consider a scheduling problem involving a single processor utilized by two customers with constant deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. Traditionally, such scenarios are modeled by assuming that each customer has the same criterion. In practice, this assumption may not hold. Instead of using a single criterion, we examine the implications of minimizing an aggregate scheduling objective function in which jobs belonging to different customers are evaluated with their individual criteria. We examine three basic scheduling criteria： minimizing makespan, minimizing maximum lateness, and minimizing total weighted completion time. We demonstrate all the scheduling problems considered are polynomially solvable.
文摘Stochastic dynamic job shop scheduling pro- blem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90 % and setup times less than processing times. Results indicate that shortest setup time （SIMSET） rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date （JMEDD） rule provides the best performance for make- span, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.
