Unbounded parallel-batch scheduling with family jobs and delivery coordination

Authors:
Shisheng Li;Jinjiang Yuan;Baoqiang Fan
Affiliations:
Department of Mathematics, Zhengzhou University, Zhengzhou 450001, PR China;Department of Mathematics, Zhengzhou University, Zhengzhou 450001, PR China;Department of Mathematics, Zhengzhou University, Zhengzhou 450001, PR China and Department of Mathematics and Information, Ludong University, Yantai 264025, PR China
Venue:
Information Processing Letters
Year:
2011

Citing 10
Cited 0

Efficient algorithms for scheduling semiconductor burn-in operations

Operations Research
Open Shop Scheduling to Minimize Finish Time

Journal of the ACM (JACM)
Supply chain scheduling: Batching and delivery

Operations Research
Integrated Scheduling of Production and Distribution Operations

Management Science
Supply chain scheduling: sequence coordination

Discrete Applied Mathematics - Special issue: International symposium on combinatorial optimization CO'02
The Integrated Production and Transportation Scheduling Problem for a Product with a Short Lifespan

INFORMS Journal on Computing
Integrated Production and Outbound Distribution Scheduling: Review and Extensions

Operations Research
Unbounded parallel batch scheduling with job delivery to minimize makespan

Operations Research Letters
The bounded single-machine parallel-batching scheduling problem with family jobs and release dates to minimize makespan

Operations Research Letters
Efficient scheduling algorithms for a single batch processing machine

Operations Research Letters

Quantified Score

Hi-index	0.89

Visualization

Abstract

We study a scheduling problem that integrates parallel-batch production with family jobs and job delivery at the same time. The jobs are first processed on an unbounded parallel-batch machine and then delivered in batches to their specified customers by a transportation vehicle. We assume that jobs from different families (customers) cannot be processed together by the batch machine and also transported together by the vehicle. The objective is to minimize the time when the vehicle finishes delivering the last delivery batch to its customer and returns to the machine. We first show that the problem is NP-hard, and then propose for it a heuristic algorithm with a worst-case performance ratio of 3/2.