• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.8
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• pp.907-914
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• 2014

A heuristic search algorithm is proposed to plan a collision free path for robots in an indoor environment. The proposed algorithm is to find a collision free path in the gridded configuration space by proposed heuristic graph search algorithm. The proposed algorithm largely consists of two parts : tunnel searching and path searching in the tunnel. The tunnel searching algorithm finds a thicker path from start grid to goal grid in grid configuration space. The tunnel is constructed with large grid defined as a connected several minimum size grids in grid-based configuration space. The path searching algorithm then searches a path in the tunnel with minimum grids. The computational time of the proposed algorithm is less than the other graph search algorithm and we analysis the time complexity. To show the validity of the proposed algorithm, some numerical examples are illustrated for robot.

• Journal of Information Processing Systems
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• v.5 no.4
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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.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.127-138
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• 1993

The Production Switching Heuristic (PSH) develope dby Mellichamp and Love (1978) has been suggested as a more realistic, practical and intuitively appealing approach to aggregate production planning (APP). In this researh, PSH has been modified to present a more sophisticated open grid search procedure for solving the APP problem. The effectiveness of this approach has been demonstrated by determining a better near-optimala solution to the classic paint factory problem. The performance of the modified production switching heuristic is then compared in the context of the paint factory problem with results obtained by other prominent APP models including LDR, PPP, and PSH to conclude that the modified PSH offers a better minimum cost solution than the original PSH model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.812-815
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• 1996

In this paper, we consider the optimal control problem based on Discrete Event Dynamic Systems(DEDS) in the Temporal Logic framework(TLF) which have studied for a convenient modeling technique. The TLF is enhanced with objective functions(event cost indices) and a measurement space is also defined. Our research goal is the design of the optimal controller for DEDSs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.25-33
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• 1997

A DEDS is a system whose states change in response to the occurence of events from a predefined event set. In this paper, we consider the optimal control and reasoning problem for Discrete Event Systems(DES) in the Temporal Logic Framework(TEL) which have been recnetly defined. The TLE is enhanced with objective functions(event cost indices) and a measurement space is alos deined. A sequence of event which drive the system form a give initial state to a given final state is generated by minimizing a cost functioin index. Our research goal is the reasoning of optimal trajectory and the design of the optimal controller for DESs. This procedure could be guided by the heuristic search methods. For the heuristic search, we suggested the Stochastic Ruler algorithm, instead of the A algorithm with difficulties as following ; the uniqueness of solutions, the computational complexity and how to select a heuristic function. This SR algorithm is used for solving the optimal problem. An example is shown to illustrate our results.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.137-150
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• 2009

This paper proposes the hybrid heuristic method to apply the opportunity time to solve the vehicle routing and scheduling problem with time constraints(VRSPTW). The opportunity time indicates the idle time which remains after the vehicle performs the unloading service required by each customer's node. In this proposed heuristic, we add the constraints to VRSPTW model for the opportunity time. We also obtain the initial solution by applying the cost evaluation function to the insertion strategy considering the opportunity time. In addition, we improve the former result by applying the opportunity time to the tabu search strategy by swapping the customer's node. Finally, we suggest the construction strategies of initial routing which can efficiently acquire the nearest optimal solution from various types of data in terms of geographical condition, scheduling horizon and vehicle capacity. Our experiment show that our heuristic can get the nearest optimal solution more efficiently than the Solomon's I1 heuristic.

• IE interfaces
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• v.21 no.1
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• pp.8-17
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• 2008

A new search procedure, VLT(Vertex Line Tracing) heuristic, for two dimensional irregular shapes nesting problem was suggested in this study. The VLT heuristic was suggested to the nesting problem to overcome disadvantages of the existing NFP(No-Fit-Polygon) method. This VLT heuristic was compared with the results of the existing benchmark problems suggested by Albano, Hopper, and Burke. The results of the VLT heuristic give efficient solutions in the point of the scrap ratio and computation time. A computer program, NestLogic, using C++ for VLT heuristic was also developed for this nesting problem.

• Korean Management Science Review
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• v.14 no.1
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• pp.31-52
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• 1997

The Generalized Assignment Problem(GAP) determines the minimum assignment of n tasks to m workstations such that each task is assigned to exactly one workstation, subject to the capacity of a workstation. In this paper, we presented a new heuristic search algorithm for GAPs. then we tested it on 4 different benchmark sample sets of random problems generated according to uniform distribution on a microcomputer.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.1
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• pp.31-31
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• 1989

The Generalized Assignment Problem(GAP) determines the minimum assignment of n tasks to m workstations such that each task is assigned to exactly one workstation, subject to the capacity of a workstation. In this paper, we presented a new heuristic search algorithm for GAPs. Then we tested it on 4 different benchmark sample sets of random problems generated according to uniform distribution on a microcomputer.

• Industrial Engineering and Management Systems
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• v.8 no.4
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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.