• Title/Summary/Keyword: Scheduling Optimization

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An Offloading Scheduling Strategy with Minimized Power Overhead for Internet of Vehicles Based on Mobile Edge Computing

  • He, Bo;Li, Tianzhang
    • Journal of Information Processing Systems
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    • v.17 no.3
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    • pp.489-504
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    • 2021
  • By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

An Optimization Model for O&M Planning of Floating Offshore Wind Farm using Mixed Integer Linear Programming

  • Sang, Min-Gyu;Lee, Nam-Kyoung;Shin, Yong-Hyuk;Lee, Chulung;Oh, Young-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.12
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    • pp.255-264
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    • 2021
  • In this paper, we propose operations and maintenance (O&M) planning approach for floating offshore wind farm using the mathematical optimization. To be specific, we present a MILP (Mixed Integer Linear Programming that suggests the composition of vessels, technicians, and maintenance works on a weekly basis. We reflect accessibility to wind turbines based on weather data and loss of power generation using the Jensen wake model to identify downtime cost that vary from time to time. This paper also includes a description of two-stage approach for maintenance planning & detailed scheduling and numeric analysis of the number of vessels and technicians on the O&M cost. Finally, the MILP model could be utilized in order to establish the suitable and effective maintenance planning reflecting domestic situation.

OPTIMAL PERIOD SELECTION TO MINIMIZE THE END-TO-END RESPONSE TIME

  • SHIN M.;LEE W.;SUNWOO M.
    • International Journal of Automotive Technology
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    • v.6 no.1
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    • pp.71-77
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    • 2005
  • This paper presents a systematic approach which determines the optimal period to minimize performance measure subject to the schedulability constraints of a real-time control system by formulating the scheduling problem as an optimal problem. The performance measure is derived from the summation of end-to-end response times of processed I/Os scheduled by the static cyclic method. The schedulability constraint is specified in terms of allowable resource utilization. At first, a uniprocessor case is considered and then it is extended to a distributed system connected through a communication link, local-inter network, UN. This approach is applied to the design of an automotive body control system in order to validate the feasibility through a real example. By using the approach, a set of optimal periods can easily be obtained without complex and advanced methods such as branch and bound (B&B) or simulated annealing.

Mathematical Model of Aquaculture Facility Utilization (양식장 이용에 대한 수학적 모형)

  • Eh, Youn-Yang
    • Journal of Fisheries and Marine Sciences Education
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    • v.26 no.2
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    • pp.444-454
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    • 2014
  • The range of optimization problem in aquaculture is very wide, resulting from the range of species, mode of operation. Quite a few studies focus marine net-cages, but studies on land based culture farm are few or no. This paper considers a allocation problem to meet production planning in land based aquaculture system. A water pool allocation model in land based aquaculture system was developed. The solution finds the value of decision variable to minimize yearly production costs that sums up the water pool usage cost and sorting cost. The model inputs were (1) the fish growth rate (2) critical standing corp (3) number of water pool (4) number of fish. The model outputs were (5) number of water pool in growing phase (6) cost of cultivation (6) optimal facility allocation(number of water pool for each growing phase). To solve the problem, an efficient heuristic algorithm based on a greedy manner is developed. Branch and bound and heuristic is evaluated through numerical examples.

An Optimization of Ship Building Mix under N Different Docks (N개의 다른 도크를 고려한 선박 건조 혼합의 최적화)

  • Kim, Yearn-Min
    • IE interfaces
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    • v.22 no.1
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    • pp.38-43
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    • 2009
  • This paper deals with two most important problems, from both practical and theoretical standpoints, arising when building the ships in N different docks. Such docks have become core components of modern ship construction. One problem is to minimize the number of building docks in the shipyard, while the other is to keep the usage rate of resources fed into docks as constant as possible. In this paper the combined problem is formulated as a single-integer programming model. The LP-relaxation of this model is solved by column-generation techniques. Practical applications of this formulation are also discussed.

A Game Theoretic Cross-Layer Design for Resource Allocation in Heterogeneous OFDMA Networks

  • Zarakovitis, Charilaos C.;Nikolaros, Ilias G.;Ni, Qiang
    • IEIE Transactions on Smart Processing and Computing
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    • v.1 no.1
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    • pp.50-64
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    • 2012
  • Quality of Service (QoS) and fairness considerations are undoubtedly essential parameters that need to be considered in the design of next generation scheduling algorithms. This work presents a novel game theoretic cross-layer design that offers optimal allocation of wireless resources to heterogeneous services in Orthogonal Frequency Division Multiple Access (OFDMA) networks. The method is based on the Axioms of the Symmetric Nash Bargaining Solution (S-NBS) concept used in cooperative game theory that provides Pareto optimality and symmetrically fair resource distribution. The proposed strategies are determined via convex optimization based on a new solution methodology and by the transformation of the subcarrier indexes by means of time-sharing. Simulation comparisons to relevant schemes in the literature show that the proposed design can be successfully employed to typify ideal resource allocation for next-generation broadband wireless systems by providing enhanced performance in terms of queuing delay, fairness provisions, QoS support, and power consumption, as well as a comparable total throughput.

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A supply planning model based on inventory-allocation and vehicle routing problem with location-assignment (수송경로 문제를 고려한 물류최적화모델의 연구)

  • 황흥석;최철훈;박태원
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1997.10a
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    • pp.201-204
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    • 1997
  • This study is focussed on optimization problems which require allocating the restricted inventory to demand points and assignment of vehicles to routes in order to deliver goods for demand sites with optimal decision. This study investigated an integrated model using three step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations. we developed several sub-models such as; first, an inventory-allocation model, second a vehicle-routing model based on clustering and a heuristic algorithms, and last a vehicle routing scheduling model, a TSP-solver, based on genetic algorithm. Also, for each sub-models we have developed computer programs and by a sample run it was known that the proposed model to be a very acceptable model for the inventory-allocation and vehicle routing problems.

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Toward Global Optimum of Part Ordering in a Flexible Manufacturing System (FMS에서의 투입부품의 최적 순서결정에 관한 연구)

  • Lee, Young-Hae; Iwata, K.
    • Journal of Korean Institute of Industrial Engineers
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    • v.16 no.2
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    • pp.51-62
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    • 1990
  • One of the important scheduling and control problems that must be solved for the efficient operation of FMS could be the "part ordering problem" which is finding optimal sequence of parts to be released into a manufacturing system. In this paper an approach which solves the problem using simulation-optimization technique will be presented. Currently available heuristic approaches for dispatching rules can only get the near optimum at the local level because of the complexities of the system and the dependencies of its components whereas the proposed approach will try to get the global optimum for a given criterion.

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Heterogeneous Multiple Traveling Purchaser Problem with Budget Constraint (예산 제약을 고려한 다용량 복수 순회구매자 문제)

  • Choi, Myung-Jin;Lee, Sang-Heon
    • Journal of the Korean Operations Research and Management Science Society
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    • v.35 no.1
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    • pp.111-124
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    • 2010
  • In the last decade, traveling purchaser problem (TPP) has received some attention of the researchers in the operational research area. TPP is a generalization of the well-known traveling salesman problem (TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. In this paper we suggest heterogeneous multiple traveling purchaser problem with budget constraint (HMTPP-B) which looks for several cycles starting at and ending to the depot and visiting a subset at a minimum traveling cost and such that the demand for each product is satisfied and the cost spent for purchasing the products does not exceed a given budget threshold. All the past studies of TPP are restricted on a single purchaser. Therefore we randomly generated some instances. CPLEX is used for getting optimal solutions in these experiments.

Uncapacitated Multiple Traveling Purchaser Problem (용량제약이 없는 복수 순회구매자 문제)

  • Choi, Myung-Jin;Lee, Sang-Heon
    • Journal of Korean Institute of Industrial Engineers
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    • v.36 no.2
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    • pp.78-86
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    • 2010
  • The traveling purchaser problem(TPP) is a generalization of the well-known traveling salesman problem(TSP), which has many real-world applications such as purchasing the required raw materials for the manufacturing factories and the scheduling of a set of jobs over some machines, and many others. TPP also could be extended to the vehicle routing problem(VRP) by incorporating additional constraints such as multi-purchaser, capacity, distance and time restrictions. In the last decade, TPP has received some attention of the researchers in the operational research area. However it has not received the equivalent interest as much as TSP and VRP. Therefore, there does not exist a review of the TPP. The purpose of this paper is to review the TPP and to describe solution procedures proposed for this problem. We also introduce the ILP formulation for the multiple TPP(mTPP) which is generalized type of TPP. We compare the system performance according to change from TPP to mTPP.