• 품질경영학회지
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• 제17권1호
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• pp.35-47
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• 1989

This paper is concerned with a development and evaluation of heuristic algorithms for the n-job, M-stage flowshop with sequence dependent setup times. Three heuristic algorithms, CAIDAN, DANNEN and PETROV, are proposed. The makespan is taken as a performance measure for the algorithms. The experiment for each algorithm is designed for a $4{\times}3{\times}3$ factorial design with 360 observations. The experimental factors are PS (ratio of processing times to setup times), M (number of machines), and N (number of jobs). The makespan of the proposed heuristic algorithms is compared with the optimal makespan obtained by the complete enumeration method. The result of comparision of performance measure is called a relative error. The mean relative errors of CAIDAN, DANNEN and PETROV algorithms are 4.488%. 6.712% and 7.282%, respectively. The computational results are analysed using SPSS. The experimental results show that the three factors are statistically signiticant at 5% level.

• 산업경영시스템학회지
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• 제32권4호
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• pp.142-152
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• 2009

We developed two heuristic methods to solve the problem considering a fleet of ships delivering chemical products from terminals to terminals. We need to decide how much of each product to carry, on which ship, subject to the conditions that all terminals must have sufficient products to meet demand, and the stock levels of the products cannot exceed the inventory capacity of that terminal. Mathematical formulation and the optimal objective value for the small size problems are compared with two greedy heuristic methods developed in terms of solution qualities and computing time. Numerical experiments on test problems indicate that the heuristics are effective at finding good solutions quickly.

• 한국통신학회논문지
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• 제41권10호
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• pp.1244-1246
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• 2016

정보 확산 극대화 문제는 소셜 네트워크에서 정보 확산을 최대로 할 수 있는 Seed 노드 군을 설정하는 것이다. 기존의 Greedy 알고리즘은 최적에 근접한 해를 제시하였으나 높은 계산량의 문제가 있다. 몇몇 Heuristic 알고리즘들이 계산량 감소를 목표로 제안되었으나 정보 확산 성능 측면에서 한계점이 있다. 본 논문에서는 General Degree Discount 알고리즘을 제안하고, 제안된 알고리즘이 계산량 측면 및 정보 확산 성능 측면에서 기존 Heuristic 알고리즘 대비 우수한 성능을 보임을 입증하고자 한다.

• Industrial Engineering and Management Systems
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• 제8권4호
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• pp.239-246
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• 2009

This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.

• 산업기술연구
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• 제28권A호
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• pp.51-61
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• 2008

In these days, domestic manufacturers are faced with managerial difficulties such as the increasing competition in their industry and the increasing power of customers. In this situation, they have to satisfy their customers with high quality of their products and meeting due date of their orders. Production of the order within due date is an important factor for improving enterprise competitiveness. The causes of occurrence of tardiness may be wrong product scheduling, unexpected events in field and so on, a way to minimize tardiness is use of alternative machines, overwork, outsourcing and etc.. In this study, we deal with a scheduling problem that can minimize tardiness using alternative machines. This paper provides a mathematical program and a heuristic method for job shop scheduling for minimizing tardiness with alternative machines. And a proposed heuristic method is verified comparing with optimal solution obtained by ILOG CPLEX.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.59-71
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• 2005

In this paper we address a design problem for hub and spoke transportation networks and then consider a capacitated hub locations problem with direct shipment (CHLPwD). We determine the location of hubs, the allocation of nodes to hubs, and direct shipment paths in the network, with the objective of minimizing the total cost in the network. An evolutionary algorithm is developed here to solve the CHLPwD. To do this, we propose the representation and the genetic operators suitable for the problem and adopt a heuristic method for the allocation of nodes to hubs. To enhance the search capability, problem-specific information is used in our evolutionary algorithm. The proposed algorithm is compared with the heuristic method in terms of solution quality and computation time. The experimental results show that our algorithm can provide better solutions than the heuristic.

• Journal of Information Processing Systems
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• 제5권4호
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• pp.237-242
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• 2009

The classical vehicle routing problem (VRP) can be extended by including customers who want to send goods to the depot. This type of VRP is called the vehicle routing problem with pickups and deliveries (VRPPD). This study proposes a novel way to solve VRPPD by introducing a two-phase heuristic routing algorithm which consists of a clustering phase and uses the geometrical center of a cluster and route establishment phase by applying a two-way search of each route after applying the TSP algorithm on each route. Experimental results show that the suggested algorithm can generate better initial solutions for more computer-intensive meta-heuristics than other existing methods such as the giant-tour-based partitioning method or the insertion-based method.

• 품질경영학회지
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• 제32권4호
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• pp.125-139
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• 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.

• 대한산업공학회지
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• 제33권4호
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• pp.447-456
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• 2007

The ant colony optimization (ACO) is a probabilistic Meta-heuristic algorithm which has been developed in recent years. Originally ACO was used for solving the well-known Traveling Salesperson Problem. More recently, ACO has been used to solve many difficult problems. In this paper, we develop an ant colony optimization method to solve the maximum independent set problem, which is known to be NP-hard. In this paper, we suggest a new method for local information of ACO. Parameters of the ACO algorithm are tuned by evolutionary operations which have been used in forecasting and time series analysis. To show the performance of the ACO algorithm, the set of instances from discrete mathematics and computer science (DIMACS)benchmark graphs are tested, and computational results are compared with a previously developed ACO algorithm and other heuristic algorithms.

• 경영과학
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• 제12권2호
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• pp.89-103
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• 1995

Traditionally, the scarce and expensive resources in communication networks has been the bandwidth of transmission facilities; accordingly, the techniques used for networking and switching have been chosen so as to optimize the efficient use of that resource. One of them is the packet switching for data communications, which is much different from the circuit switching. It allows multiple users to share the data network facilities and bandwidth, rather than providing specific amounts of dedicated bandwidth to each users. One main challenge therefore has been to design and build cost-effective packet switching networks. In this paper, we develop a mathematical programming medel and heuristic algorithm for designing the packet switching networks with hop-count constraints. To develop an efficient heuristic, we apply the Lagrangian relaxation method. Some valid inequalities, which have been known as the tight constraints, are considered to improve the bound for Lagrangian sub-problem. The computational experiments show that the performance of the proposed heuristic is very satisfactory in both the speed and the quality of design solutions generated.