• Journal of Information Processing Systems
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• 제10권2호
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• pp.193-214
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• 2014

Load balancing is the major benefit of any distributed system. To facilitate this advantage, task duplication and migration methodologies are employed. As this paper deals with dependent tasks (DAG), we used duplication. Task duplication reduces the overall schedule length of DAG along-with load balancing. This paper proposes a new task duplication algorithm at the time of tasks assignment on various processors. With the intention of conducting proposed algorithm performance computation; simulation has been done on the Netbeans IDE. The mesh topology of a distributed system is simulated at this juncture. For task duplication, overall schedule length of DAG is the main parameter that decides the performance of a proposed duplication algorithm. After obtaining the results we compared our performance with arbitrary task assignment, CAWF and HEFT-TD algorithms. Additionally, we also compared the complexity of the proposed algorithm with the Duplication Based Bottom Up scheduling (DBUS) and Heterogeneous Earliest Finish Time with Task Duplication (HEFT-TD).

• Industrial Engineering and Management Systems
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• 제7권2호
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• pp.171-181
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• 2008

Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.

• 대한산업공학회지
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• 제25권1호
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• pp.21-34
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• 1999

We consider a scheduling problem arising in a shipyard subassembly welding process. There are four welding robots of gantry type, which perform the welding process for the subassemblies. Because the robots perform the welding operations at the same time, there is a possibility of collision between adjacent robots depending on the welding schedule. In this paper, we propose a heuristic method to find a welding schedule which does minimize the welding completion time while avoiding collision among the robots. The method consists of two phases: assignment and scheduling. In the assignment phase, we assign each welding line to a proper robot. In the scheduling phase, we determine the welding schedules for the robots so that collision is avoided. Computational experiences with the data which reflect the real situation are reported.

• 산업경영시스템학회지
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• 제11권17호
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• pp.39-46
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• 1988

This Paper is concerned with a man-multi machine assignment problem to minimize idle time. Assuming different types of semi-automatic machines with deterministic service-processing time, the problem approaches by sequential dependent one operator can handle several machines, where determine optimal range the cost of idle labor and machine time is to be minimized in preparing a work schedule. The Procedure, to establish man-machine assignment model, and it's results are: (1) Objective function to minimize opportunity loss cost, which is happened by idle time, is verified recursive process through heuristic method. (2) The algorithm, is programmed by BASIC language for personal computer, and a numerical example is given to illustrate the heuristic algorithm. This study will be helpful to enhance productivity of Shopflooras a result of increasing the efficiencies of both operator and machine.

• Management Science and Financial Engineering
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• 제11권2호
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• pp.19-43
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• 2005

This paper considers a variation of the customer order scheduling problem, and the variation is the case where the machine-job assignment is fixed. We examine the parallel machine environment, and the objective is to minimize the sum of the completion times of the batches. While a machine can process only one job at a time, different machines can simultaneously process different jobs in a batch. The recognition version of this problem is known to be NP-complete in the strong sense even if there exist only two parallel machines. When there are an arbitrary number of parallel machines, we establish three lower bounds and develop a dynamic programming (DP) algorithm which runs in exponential time on the number of batches. We present two simple but intuitive heuristics, SB and GR, and find some special cases where SB and GR generate an optimal schedule. We also find worst case upper bounds on the relative error. For the case of the two parallel machines, we show that GR generates an optimal schedule when processing times of all batches are equal. Finally, the heuristics and the lower bounds are empirically evaluated.

• 제어로봇시스템학회논문지
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• 제11권2호
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• pp.175-185
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• 2005

The scheduling methods of the distributed real-time systems have been proposed. However, they have some weak points. They did not schedule both sporadic and periodic tasks and messages at the same time or did not consider the end-to-end constraints such as precedence relations between sporadic tasks. This means that system scheduling must guarantee the constraints of practical systems and be applicable to them. This paper proposes a new scheduling method that can be applied to more practical model of distributed real-time systems. System model consists of sporadic and periodic tasks with precedence relations and sporadic and periodic messages and has end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• 대한산업공학회지
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• 제41권1호
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• pp.1-9
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• 2015

In shipbuling processes, a quay wall is a major resource for additional operations after an erection operation at dock. A quay wall is becoming a new bottleneck instead of docks, while ship types with long operation time at quay wall are increasing recently. We developed a quay wall scheduling algorithm for the quayside operations of ships in this paper. The objective function is to minimize the sum of not assigned days of ships which have to be assigned to any quay wall under limited numbers of quay walls. The scheduling algorithm is based on an assignment method to assign each ship to a quay wall among its alternative quay walls at the time of launching or moving to another quay wall. The scheduling algorithm is also using Tabu Search algorithm to optimize assignment sequence of ships. The experiment shows that the algorithms in this paper are effective to make schedule of the quayside operations of ships.

• Industrial Engineering and Management Systems
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• 제14권3호
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• pp.299-311
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• 2015

Nowadays, the distribution centres aim to reduce costs by reducing inventory and timely shipment. Cross docking is a logistics strategy in which products delivered to a distribution centre by inbound trucks are directly unloaded and transferred to outbound trucks with minimum warehouse storage. Moreover, on-time delivery in a distribution network becomes very crucial especially when several distribution centres and customers are involved. Therefore, an efficient truck scheduling is needed to synchronize the delivery throughout the network in order to satisfy all stake-holders. This paper presents a mathematical model of a mixed integer programming for door assignment and truck scheduling in a multiple inbound and outbound doors cross docking problem according to Just-In-Time concept. The objective is to find the schedule of transhipment operations to simultaneously minimize the total earliness and total tardiness of trucks. Then, a multi-objective differential evolution (MODE) is proposed with an encoding scheme and four decoding strategies, called ITSH, ITDD, OTSH and OTDD, to find a Pareto frontier for the multi-door cross docking problems. The performances of MODE are evaluated using 15 generated instances. The numerical experiments demonstrate that the proposed algorithm is capable of finding a set of diverse and high quality non-dominated solutions.

• 한국인공지능학회지
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• 제9권1호
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• pp.1-7
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• 2021

In this paper, We focused the issue of creating a socially problematic nurse schedule. The nurse schedule should be prepared in consideration of three shifts, appropriate placement of experienced workers, the fairness of work assignment, and legal work standards. Because of the complex structure of the nurse schedule, which must reflect various requirements, in most hospitals, the nurse in charge writes it by hand with a lot of time and effort. This study attempted to automatically create an optimized nurse schedule based on legal labor standards and fairness. We developed an I/O Q-Learning algorithm-based model based on Python and Web Application for automatic nurse schedule. The model was trained to converge to 100 by creating an Fairness Indicator Score(FIS) that considers Labor Standards Act, Work equity, Work preference. Manual nurse schedules and this model are compared with FIS. This model showed a higher work equity index of 13.31 points, work preference index of 1.52 points, and FIS of 16.38 points. This study was able to automatically generate nurse schedule based on reinforcement Learning. In addition, as a result of creating the nurse schedule of E hospital using this model, it was possible to reduce the time required from 88 hours to 3 hours. If additional supplementation of FIS and reinforcement Learning techniques such as DQN, CNN, Monte Carlo Simulation and AlphaZero additionally utilize a more an optimized model can be developed.

• 품질경영학회지
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• 제50권2호
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• pp.265-286
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• 2022

Purpose: The time and cost of a project activity exists in a selected mode and there is a quality level for the selected mode, and the time and cost of the current activity is determined by the quality level of the preceding activity. When an activity is a predecessor activity of an activity, it is characterized as a trade-off problem in which the time and cost of the activity are determined according to the quality level of the activity. Methods: A neighbor search heuristic algorithm obtains a solution by (1) randomly determining the mode, quality level, and assignment order for each activity. (2) get a solution by improving the solution by changing the possible modes and quality levels; (3) to find a solution by improving the solution from the point where it is feasible to advance the start time. Here, Case[1] is a method to find the optimal solution value after repeating (1). Case [2] is a method for finding a solution including (1) and (2). Case [3] refers to a method for finding solutions including (1), (2), and (3). Results: It can be seen that the value of the objective function presented by the algorithm changes depending on how the model of the heuristic algorithm is designed and applied. In other words, it suggests the importance of algorithm design and proves the importance of the quality problem of activities in the project schedule. Conclusion: A study significance of the optimization algorithm and the heuristic algorithm was applied to the effect of the quality of the preceding activity on the duration and cost of itself and the succeeding activity, which was not addressed in the project schedule problem.