• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.20 no.44
• /
• pp.1-12
• /
• 1997

In this paper a new heuristic algorithm has been developed and presented for minimizing the total completion time of a scheduling problem in a multi stage automated machining and assembly systems. The proposed Higher Ratio First(HRF) algorithm is based on the idea that jobs with higher processing time ratio should be a higher priority. The heuristic algorithm is implemented on the various problem cases by number of jobs and machines. The proposed algorithm provided smaller makespan than the makespan applied by three previously documented heuristics. The results obtained show a superior solution by the new heuristic over previous heuristics on all problem sizes.

• Journal of National Security and Military Science
• /
• s.1
• /
• pp.345-360
• /
• 2003

To build an information oriented armed forces, the Korean military telecommunication networks adopt TCP/IP standard communication infrastructures based on ATM packet switched networks. Utilizing this network infrastructure, the Korean armed forces also applies to the areas of battleship management for efficient operation command controls and resource management for efficient resource allocations. In this military communication networks, it is essential to determine the least cost network topology under equal performance and reliability constraints. Basically, this type of communication network design problem is known in the literature as an NP Hard problem. As the number of network node increases, it is very hard to obtain an optimal solution in polynomial time. Therefore, it is reasonable to use a heuristic algorithm which provides a good solution with minimal computational efforts. In this study, we developed a simulated annealing based heuristic algorithm which can be utilized for the design of military communication networks. The developed algorithm provides a good packet switched network topology which satisfies a given set of performance and reliability constraints with reasonable computation times.

• Journal of Korean Institute of Industrial Engineers
• /
• v.34 no.2
• /
• pp.205-215
• /
• 2008

convergence networks (BcN). The problem seeks to minimize the total cost of switch and cable while satisfying the requirement of demand and quality of service (QoS). We develop mixed integer programming models to obtain the optimal switch location of the access network. We develop a Tabu Search (TS) heuristic algorithm for finding a good feasible solution within a reasonable time limit. We propose real networks with up to 25 nodes and 180 demands. In order to demonstrate the effectiveness of the proposed algorithm, we generate lower bounds from nonlinear QoS relaxation problem. Computational results show that the proposed heuristic algorithm provides upper bounds within 5% optimality gap in 10 seconds.

• Journal of Korean Society for Quality Management
• /
• v.32 no.4
• /
• pp.125-139
• /
• 2004

Generally, parallel redundancy is used to improve reliability in many systems. However, redundancy increases system cost, weight, volume, power, etc. Due to limited availability of these resources, the system designer has to maximize reliability subject to various constraints or minimize resources while satisfying the minimum requirement of system reliability. This paper presents GAs (Genetic Algorithms) to solve redundancy allocation in series-parallel systems. To apply the GAs to this problem, we propose a genetic representation, the method for initial population construction, evaluation and genetic operators. Especially, to improve the performance of GAs, we develop heuristic operators (heuristic crossover, heuristic mutation) using the reliability-resource information of the chromosome. Experiments are carried out to evaluate the performance of the proposed algorithm. The performance comparison between the proposed algorithm and a pervious method shows that our approach is more efficient.

• Journal of Korean Institute of Industrial Engineers
• /
• v.12 no.2
• /
• pp.77-87
• /
• 1986

This paper presents a heuristic method for solving the discrete-time ordering problem with quantity discounts and deterministic, time-varying demand. This algorithm utilizes a variation of the incremental cost approach(ICA) to determine a near optimal solution. The ICA is the method which reduces the total cost with reduction of the number of orders by one. In order to reduce the number of orders, if the incremental cost for one of the periods is negative, the demand of the period should be purchased in its immediate preceding period. In order to test the performance of this algorithm, an experiment is conducted that involves a large number of test problems covering a wide variety of situations. The result of the experiment shows that the proposed algorithm has 80.5% better solutions than the adjusted part period algorithm(APPA), which is known to be the best heuristic method.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.61
• /
• pp.105-114
• /
• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• Journal of the military operations research society of Korea
• /
• v.24 no.2
• /
• pp.117-129
• /
• 1998

This study is concerned with developing a heuristic for a web-based vehicle routing problem using mixed genetic algorithm(VRPMGA) which determines each vehicle route in order to minimize the transportation costs, subject to meeting the demands of all delivery points. VRP is known to be NP-hard, and it needs a lot of computing time to get the optimal solution, so that heuristics are more frequently developed than optimal algorithms. This study aims to develop a mixed genetic algorithm by partitioned strategy which can give a good solution in comparatively brief time. The good features of the VRPMGA are, fristly, the ability of early convergence and, secondly, the capability of producing multiple, alternative, and near-optimal solutions. The VRPMGA is a useful algorithm that can be appliable to VRP and TSP. Finally, the computational test were performed using the benchmark problems and the proposed heuristic is compared with the other existing algorithms (COSA). The result of computational tests shows that proposed heuristic gives good solutions, in much shorter time, which are same as the best known solutions in the pervious research.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.22 no.53
• /
• pp.23-35
• /
• 1999

Since on-time delivery is becoming increasingly important in today's competitive markets, the development of effective scheduling methodologies to meet customer needs through on time delivery is of vital importance for the well-being of companies. The objective of this study is to develope a general heuristic algorithm for scheduling both the static and dynamic problems under certain on-time delivery criteria. For the problems with due-date related, we present insights for minimizing the number of tardy jobs and propose a heuristic scheduling algorithm. Experimental results show that the proposed algorithm performs significantly better than other dispatching rules within reasonable computation time, specially in the environment of strong competition for resources.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.21 no.45
• /
• pp.165-180
• /
• 1998

To make a scheduling for minimizing the tardiness of delivery, we present an efficient heuristic algorithm for job-shop scheduling problems with due dates. The SDME(Slack Degree Modified Exchange) algorithm, which is the proposed heuristic algorithm, carries out the operation in two phases. In the phase 1, a dispatching rule is employed to generate an active or non-delay initial schedule. In the phase 2, tasks selected from a predetermined set of promising target operations in the initial schedule are tested to ascertain whether, by left-shifting their start times and rearranging some subset of the remaining operations, one can reduce the total tardiness. In the numerical example, the results indicate that the proposed SDME algorithm is capable of yielding notable reductions in the total tardiness for practical size problems.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.28 no.3
• /
• pp.156-165
• /
• 2005

A new heuristic algorithm for the heterogeneous single container loading problem is proposed in this paper, This algorithm fills empty spaces with the homogeneous load-blocks of identically oriented boxes and splits residual space into three sub spaces starting with an empty container. An initial loading pattern is built by applying this approach recursively until all boxes are exhausted or no empty spaces are left. In order to generate alternative loading patterns, the load-blocks of pattern determining spaces are replaced with the alternatives that were generated on determining the load-blocks. An improvement algorithm compares these alternatives with the initial pattern to find improved one. Numerical experiments with 715 test cases show the good performance of this new algorithm, above all for problems with strongly heterogeneous boxes.