• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.711-713
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• 1996

This paper proposes a unit commitment scheduling method based on Genetic Algorithm(GA). Due to a variety of constraints to be satisfied, the search space of the UC problem is highly nonconvex, so the UC problem cannot be solved efficiently only using the standard GA To efficiently deal with the constraints of the problem and greatly reduce the search space of the GA, the minimum up and down time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The violations of other constraints arc handled by integrating penalty factors. To show the effectiveness of the GA based unit commitment scheduling, test results for system of 5 units are compared with results obtained using Lagrangian Relaxation and Dynamic Programming.

• IE interfaces
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• v.24 no.1
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• pp.78-86
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• 2011

To mitigate space restriction and to raise productivity, some shipbuilding companies use floating-docks on the sea instead of dry-docks on the land. In that case, a floating-crane that can lift very heavy objects (up to 3,600 tons) is used to handle the blocks which are the basic units in shipbuilding processes, and so, very large blocks (these are called the mega-blocks) can be used to build a ship. But, because these mega-blocks can be made only in the area near the floating-dock and beside the sea, the space is very important resource for the process. Therefore, our problem is to make an efficient spatial schedule for the mega-block assembly yard. First of all, we formulate this situation into a mathematical model and find optimal solution for a small problem using a commercial optimization software. But, the software could not give optimal solutions for practical sized problems in a reasonable time, and so we propose a GA-based heuristic algorithm. Through a numerical experiment, finally, we show that the spatial scheduling algorithm can provide a very good performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1093-1105
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• 2012

We propose an interference space reuse (ISR) algorithm for the MU-MIMO design in 3-cell downlink interference channels. Also, we provide a strategy for the adoption of the ISR scheme in the cellular network. In the multicell interference channels, the cell edge users may undergo severe interferences and their signals should be protected from the interferers for reliable transmissions. However, the intra cell users do not only experience small interferences but also they require small transmission power for stable communication. We provide a vector design algorithm based on ISR, where intra cell users are served through reusing the cell edge users' interference space. The performance enhancement reaches 20% compared to the fractional frequency reuse (FFR) scheme combined with IA through the scheduling between the cell edge users and the intra cell users. Also, it can be used to enhance the cell edge throughput when the quality of service (QoS) requirements of the intra cell users are fixed.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.49-59
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• 2011

A ship scheduling model is presented for the raw material transportation problem with yard storage constraints in a steel mill. The problem is formulated as 0, 1 mixed integer programming considering such constraints as loading port conditions, ship size and hold capacity, unloading conditions, and yard storage space. In addition, inventory related constraints including safety stock are taken into consideration to support the continuous operations of steel making process. The proposed model has been implemented and applied successfully to a real world problem, and its results show the improvement of performance compared to the traditional method. For example, the arrival dates of ships are determined satisfying the constraints. The total inventory level is minimized at the stock yard as a result. Also, the safety inventory level is always kept at the planning stage, and the standard deviation of total inventory level is reduced significantly. Further research is expected to develop efficient heuristics to have a better response time for even larger scale problems.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1940-1949
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• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

• Management Science and Financial Engineering
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• v.10 no.2
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• pp.1-28
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• 2004

The integrated supply chain of business partners for e-Commerce in cyber space is defined as Logistics Chain if the cooperative activities are logistics-related. Logistics Chain could be managed effectively and efficiently by cooperative technologies of logistics chain execution. In this paper, we propose a routing and scheduling algorithm based on the Tabu search by adding geographical information into existing constraint for pick-up and delivery process to minimize service time and cost in logistics chain. And, we also consider an uncertainty processing for the tracing of moving object to control pick-up and delivery vehicles based on GPS/GIS/ITS. Uncertainty processing is required to minimize amount of telecommunication and database on vehicles tracing. Finally, we describe the Logistics Chain Execution (LCE) system to perform plan and control activities for postal logistics chain. To evaluate practical effects of the routing and scheduling system, we perform a pretest for the performance of the tabu search algorithm. And then we compare our result with the result of the pick-up and delivery routing plan generated manually by postmen.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.80-88
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• 2001

The existed approaches to analyzing real-time schedulability take place exponential time and space complexity of this methods, since these uses a fixed priority scheduling and/or traverse all possible state spaces. This paper judges whether it is satisfied a given deadlines for real-time processes regarding a minimum execution time of process, periodic, deadline and a synchronizion time of processes by using the transaction rules of process algebra, and proposes a retrieval algorithm for unschedulable processes based on GUI environment. And we implement and evaluate the scheduling state analyzer that displays visually the result of schedulabiliy analysis for real-time processes.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.93-100
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• 2004

Test scheduling of SoC (System-on-a-chip) is very important because it is one of the prime methods to minimize the testing time under limited power consumption of SoC. In this paper, a heuristic algorithm, in which test resources are selected for groups and arranged based on the size of product of power dissipation and test time together with total power consumption in core-based SoC is proposed. We select test resource groups which has maximum power consumption but does not exceed the constrained power consumption and make the testing time slot of resources in the test resource group to be aligned at the initial position in test space to minimize the idling test time of test resources. The efficiency of proposed algorithm is confirmed by experiment using ITC02 benchmarks.

• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.70-79
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• 2010

Makespan and cost minimization are two important factors in project investment. This paper considers a multi-mode resource-constrained project scheduling problem with the objective of minimizing costs, subject to a deadline constraint. A number of studies have focused on minimizing makespan or resource availability cost with a specified deadline. This problem assumes a fixed cost for the availability of each renewable resource per period, and the project cost to be minimized is the sum of the variable cost associated with the execution mode of each activity. The presented memetic algorithm (MA) consists of three features: (1) a truncated branch and bound heuristic that serves as effective preprocessing in forming the initial population; (2) a strategy that maintains two populations, which respectively store deadline-feasible and infeasible solutions, enabling the MA to explore quality solutions in a broader resource-feasible space; (3) a repair-and-improvement local search scheme that refines each offspring and updates the two populations. The MA is tested via ProGen generated instances with problem sizes of 18, 20, and 30. The experimental results indicate that the MA performs exceptionally well in both effectiveness and efficiency using the optimal solutions or the current best solutions for the comparison standard.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.