A Novel B and B Algorithm for a Unrelated Parallel Machine Scheduling Problem to Minimize the Total Weighted Tardiness
Authors
Abstract:
This paper presents a scheduling problem with unrelated parallel machines and sequencedependent setup times that minimizes the total weighted tardiness. A new branch-and-bound (B and B) algorithm is designed incorporating the lower and upper bounding schemes and several dominance properties. The lower and upper bounds are derived through an assignment problem and the composite dispatching rule (ATCS), respectively. We carry out computational experiments and the related results are reported.
similar resources
Scheduling rules to minimize total tardiness in a parallel machine problem with setup and calendar constraints
Quality control lead times are one of most significant causes of loss of time in the pharmaceutical and cosmetics industries. This is partly due to the organization of laboratories that feature parallel multipurpose machines for chromatographic analyses. The testing process requires long setup times and operators are needed to launch the process. The various controls are non-preemptive and are ...
full textDesign of a Hybrid Genetic Algorithm for Parallel Machines Scheduling to Minimize Job Tardiness and Machine Deteriorating Costs with Deteriorating Jobs in a Batched Delivery System
This paper studies the parallel machine scheduling problem subject to machine and job deterioration in a batched delivery system. By the machine deterioration effect, we mean that each machine deteriorates over time, at a different rate. Moreover, job processing times are increasing functions of their starting times and follow a simple linear deterioration. The objective functions are minimizin...
full textSingle Machine and Parallel Machine Scheduling Problems with a Common Due Date to Minimize Total Weighted Tardiness
This paper deals with a common due date parallel machines scheduling problem in which each job has a different tardiness penalty. The objective is to minimize the total weighted tardiness. The scheduling problem of minimizing the total weighted tardiness with a common due date on a single machine is known to be ordinary NP-hard. This is also the case for problem Pm|di = d| ∑ wiTi. A new dynamic...
full textA tabu search algorithm for parallel machine total tardiness problem
In this study, a Tabu Search (TS) approach to the parallel machine scheduling problem is presented. The problem considered consists of a set of independent jobs to be scheduled on a number of parallel processors to minimize total tardiness. Several surveys on parallel machine scheduling with due date related objectives [1, 2, 3] reveal that the NP-hard nature of the problem renders it a challen...
full textA branch and bound algorithm to minimize the total weighted number of tardy jobs and delivery costs with late deliveries for a supply chain scheduling problem
In this paper, we study a supply chain scheduling problem that simultaneously considers production scheduling and product delivery. jobs have to be scheduled on a single machine and delivered to customers for further processing in batches. The objective is to minimize the sum of the total weighted number of tardy jobs and the delivery costs. In this paper, we present a heuristic algorithm (HA...
full textA Cluster-based Evolutionary Algorithm for the Single Machine Total Weighted Tardiness-scheduling Problem
In this paper a new evolutionary algorithm is described for the single machine total weighted tardiness problem. The operation of this method can be divided in three stages: a cluster forming and two local search stages. In the first stage it approaches some locally optimal solutions by grouping based on similarity. In the second stage it improves the accuracy of the approximation of the soluti...
full textMy Resources
Journal title
volume 22 issue 3
pages 269- 286
publication date 2009-09-01
By following a journal you will be notified via email when a new issue of this journal is published.
Hosted on Doprax cloud platform doprax.com
copyright © 2015-2023