New Developments in Scheduling Applications

Scheduling problems are widely recognized as important optimization problems. Thus, scheduling theory has become a fundamental area within the general field of combinatorial optimization. Multiprocessor and shop scheduling problems are known to be hard to solve optimally. Scheduling problems are naturally very varied, both in application domains and in featured constraints. To date, researchers have been working on scheduling problems derived from new applications such as scheduling problems in logistical airport operations management processes, decentralized systems and selfish organizations, grid computing, and bioinformatics. These scheduling problems reflect real-life situations for including learning effects or deteriorating jobs. In the call for papers, we advised that all authors should be encouraged to focus on scheduling heuristics, scheduling with some effects such as learning and deterioration, grouping and sequencing operations in multistage systems, scheduling in flexible shops, scheduling under some constraints such as precedence, batching/lot sizing, setups, and further technologies, scheduling under uncertainty, and scheduling in a supply chain. The obtained responses gratified us with a total of 24 submissions. All of them were peer reviewed according to high standards of this journal. At the end of the process, we accepted seven papers. The accepted papers represent excellent work that spans across a wide variety of cutting edge scheduling problems and applications. D. C. Dietz proposes a study on computing the expected cost of an appointment schedule for statistically identical customers with probabilistic service times. In this paper, the author presented a cogent method to compute the expected cost of an appointment schedule. Customers are statistically identical, the service time distribution has been known as mean and variance, and no-shows occur with time-dependent probability. X. Shi and D. Xu develop a solution for single-machine scheduling with increasing linear maintenance durations by the best possible approximation algorithms. They used the linear form í µí±“(í µí±¡) = í µí±Ž+í µí±í µí±¡ with í µí±Ž ≥ 0 and í µí± > 1. They proposed an approximation algorithm named FFD-LS2I with a worst-case bound of 2 for problem. Furthermore, they also showed that there is no polynomial time approximation algorithm with a worst-case bound for the problem with í µí± ≥ 0 unless í µí±ƒ = í µí±í µí±ƒ, which implies that the FFD-LS2I algorithm is the best possible algorithm for the case í µí± > 1. T. Luo and Y. Xu investigate semionline scheduling on two machines with grade of service (GoS) levels and partial information …