박명주 교수

In labor scheduling, restaurant managers face dual challenges: overstaffing that means excessive labor costs and understaffing that invites the opportunity cost of service errors and lost business. Most operators seek to rely on their personal experience and judgment to determine schedules that are meant to maintain service quality and limit labor costs, but an analysis of one Korean restaurant finds that this goal is elusive. The labor scheduling model based on integer programming (IP) is prese

Compromising productivity in exchange for energy saving does not appeal to highly capitalized manufacturing industries. However, we might be able to maintain the same productivity while significantly reducing energy consumption. This paper addresses a flexible job shop scheduling problem with a shutdown (on/off) strategy aiming to minimize makespan and total energy consumption. First, an alternative mixed integer linear programming model is proposed. Second, a novel constraint programming is pro

We consider a two-machine flow shop scheduling with two properties. The first is that each due date is assigned for a specific position different from the traditional definition of due dates, and the second is that a consistent pattern exists in the processing times within each job and each machine. The objective is to minimize maximum tardiness, total tardiness, or total number of tardy jobs. We prove the strong NP-hardness and inapproximability, and investigate some polynomially solvable cases

We consider a two-agent scheduling problem in a two-machine flow shop environment where each agent is responsible for his own set of jobs and wishes to minimize the makespan. The objective is to minimize one agent’s makespan, subject to the other’s objective of not exceeding a given threshold. It is known that the problem is NP-hard. Thus, we consider special cases such that the processing times of each agent have a special structure, and analyze their computational complexity.

Abstract We consider a two-machine flow shop scheduling problem in which the processing time of each operation is inversely proportional to the power of the amount of resources consumed by it. The objective is to minimize the sum of the makespan and the total resource consumption cost. We show that the problem is NP-hard, and its constrained version remains so. Then, we develop 1.25- and 2-approximation algorithms for the problem and its constrained version, respectively.