Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Integrated Scheduling of Production and Distribution Operations
Management Science
Two-machine flowshop scheduling with job class setups to minimize total flowtime
Computers and Operations Research
A heuristic approach for tow-machine no-wait flowshop scheduling with due dates and class setups
Computers and Operations Research
Lot-sizing scheduling with batch setup times
Journal of Scheduling
Order Assignment and Scheduling in a Supply Chain
Operations Research
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Multi-product sequencing and lot-sizing under uncertainties: A memetic algorithm
Engineering Applications of Artificial Intelligence
Lowest priority first based feasibility analysis of real-time systems
Journal of Parallel and Distributed Computing
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We study machine scheduling problems in which the jobs belong to different job classes and they need to be delivered to customers after processing. A setup time is required for a job if it is the first job to be processed on a machine or its processing on a machine follows a job that belongs to another class. Processed jobs are delivered in batches to their respective customers. The batch size is limited by the capacity of the delivery vehicles and each shipment incurs a transport cost and takes a fixed amount of time. The objective is to minimize the weighted sum of the last arrival time of jobs to customers and the delivery (transportation) cost. For the problem of processing jobs on a single machine and delivering them to multiple customers, we develop a dynamic programming algorithm to solve the problem optimally. For the problem of processing jobs on parallel machines and delivering them to a single customer, we propose a heuristic and analyze its performance bound.