• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.51
• /
• pp.231-240
• /
• 1999

A major concern in Concurrent Engineering is the control and management of workload in a period of process. As a general rule, leveling the peak of workload in certain period is difficult because concurrent processing is comprised of various processes, including overlapping, paralleling looping and so on. Therefore, the workload management with resource constraints is so beneficial that effective methods to analyze design process are momentous. This study presents the Timed Petri Nets approach of precedence logic networks, and provides an alternative for users to analyze constraint processes to resolve conflicts of resources. Another approach to Continuous Time Markov Chain using Stochastic Petri Nets is also proposed. These approaches are expected to facilitate resolving resource constrained scheduling problems more systematically in Concurrent Engineering environment.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.14 no.23
• /
• pp.19-25
• /
• 1991

In this paper, constrained resource project scheduling problems schedule project activities subject to finite constraints on the availability of non-storable resource. Further, resources are assumed to be available per period in constant amounts, and are also demanded by an activity in constant amounts throughout the duration of the activity. We describe formulation which minimizes the combined cost of fluctuations in resource demand and delay of project completion. Cost bounding procedures are augmented by dominance relationships presented as theorems. This paper presents algorithm for solving the problem. And numerical examples are presented. Sensitivity analysis to evaluate the effect of changes of cost efficients is conducted.

• Journal of Information Processing Systems
• /
• v.20 no.2
• /
• pp.226-238
• /
• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.

• Journal of Korean Institute of Industrial Engineers
• /
• v.21 no.4
• /
• pp.541-553
• /
• 1995

An efficient algorithm is proposed for a buffer allocation in a continuous flow line. The problem is formulated as a non-linear programming with linear constraints. The concept of pseudo gradient and gradient projection is employed in developing the algorithm. Numerical experiments show that the algorithm gives the actual optimal solutions to the problems with single linear constraint limiting the total buffer capacity. Also, even in longer production lines, it gives quite good solutions to the problems with the general linear resource constraints within a few seconds.

• KIISE Transactions on Computing Practices
• /
• v.22 no.1
• /
• pp.1-7
• /
• 2016

When multiple applications are running concurrently on a multi-processor system, interferences between applications make it difficult to guarantee real-time constraints. We propose a novel interference analysis technique that allows sharing of share processors among dataflow applications, while satisfying real-time constraints. Based on the interference analysis, we develop a co-scheduling technique that aims to minimize the resource usage. Compared to an existent technique that involves converting application graphs to real-time tasks, the proposed technique shows better results in terms of resource usage, especially when it is applied to applications with tight time constraints.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.4
• /
• pp.424-432
• /
• 1992

This paper deals with the scheduling ploblems, which are the most important subtasks in High-level syntheses. IP(integer programming) formulations is used as the scheduling problem approach. This paper describes a new resource-constraints scheduling algorithm. We have concentrated our attentions on the multicycle operations and the structural pipelining, and we fully analyze the characteristics of operators to achieve the maximal performance and the maximal resource sharing. For experiment results, we choose the 5-th order digital wave filter as a benchmark and do the schedule, Finally, we can obtain near-optimal scheduling results.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.11
• /
• pp.4387-4404
• /
• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• Journal of Communications and Networks
• /
• v.12 no.1
• /
• pp.30-42
• /
• 2010

In this work we consider the problem of downlink resource allocation for proportional fairness of long term received rates of data users and quality of service for real time sessions in an OFDMA-based wireless system. The base station allocates available power and subchannels to individual users based on long term average received rates, quality of service (QoS) based rate constraints and channel conditions. We formulate and solve a joint bandwidth and power optimization problem, solving which provides a performance improvement with respect to existing resource allocation algorithms. We propose schemes for flat as well as frequency selective fading cases. Numerical evaluation results show that the proposed method provides better QoS to voice and video sessions while providing more and fair rates to data users in comparison with existing schemes.

• Korean Management Science Review
• /
• v.10 no.1
• /
• pp.171-192
• /
• 1993

In this paper, a rule for dispatching operations, named the Most Dissimilar Resources (MDR) dispatching rule is presented. The MDR dispatching rule has been designed to maximize utilization of resources in a resource-constrained job shop with general precedence constraints. In shown that solving the above scheduling problem with the MDR dispatching rule is equivalent to multiple solving of the maximum clique problem. A graph theoretic approach is used to model the latter problem. The pairwise counting heuristic of computational time complexity O(n$^{2}$) is developed to solve the maximum clique problem. An attempt is made to combine the MDR dispatching rule with the existing look-ahead dispatching rules. Computational experience indicates that the combined MDR dispatching rules provide solutions of better quality and consistency than the dispatching rules tested in a resource-constrained job shop.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.881-885
• /
• 2005

Scheduling repetitive projects under limitations on the amounts of available resources (labor and equipment) has been an active subject because of its practical relevance. Traditionally, the limitation is specified as a deterministic (fixed) number, such as 1000 labor-hours. The limitation, however, is often exposed to uncertainty and variability, especially when the project is lengthy. This paper presents a stochastic optimization model to treat the situations where the limitations of resources are expressed as probability functions in lieu of deterministic numbers. The proposed model transfers each deterministic resource constraint into a corresponding stochastic one and then solves the problem by the use of a chance-constrained programming technique. The solution is validated by comparison with simulation results to show that it can satisfy the resource constraints with a probability beyond the desired confidence level.