• Journal of Distribution Science
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• v.16 no.2
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• pp.19-24
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• 2018

Purpose - Drone delivery is expected to revolutionize the supply chain industry. This paper aims to introduce a collaborative parcel delivery problem by truck and drone (hereinafter called "TDRP") and propose a novel heuristic method to solve the problem. Research design, data, and methodology - To show the effectiveness of collaborative delivery by truck and drone, we generate a toy problem composed of 9 customers and the speed of drone is assumed to be two times faster than truck. We compared the delivery completion times by 'truck only' case and 'truck and drone' case by solving the optimization problem respectively. Results - We provide literature reviews for truck and drone routing problem for collaborative delivery and propose a novel and original heuristic method to solve the problem with numerical example. By numerical example, collaborative delivery is expected to reduce delivery completion time by 12~33% than 'truck only' case. Conclusions - In this paper, we introduce the TDRP in order for collaborative delivery to be effective and propose a novel and original heuristic method to solve the problem. The results of research will be help to develop effective heuristic solution and optimize the parcel delivery by using drone.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.33-45
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• 2000

The present study examined the usability of the web site design, focusing on the cognitive characteristics of the WWW. Specifically, we conducted two major non-experimental usability testing methods on the domestic web sites with various purposes. In research I. we used an on-line questionnaire method on 12 domestic web sites. As a result. several critical usability features and factors were identified. In research 2. we carried out a heuristic evaluation method to identify more specific usability problems The result of research 2 suggests that the heuristic evaluation method reveals more specific problems of the web site design than the questionnaire method.

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

• Korean Management Science Review
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• v.12 no.2
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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.

• Korean Management Science Review
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• v.10 no.2
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• pp.79-91
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• 1993

Strategic decisions related to the design of a physical distribution system can be classified into three basic components : facility location, transportation, inventory decisions. In this research the interdependence of those decisions are expressed in a mathematical model such that the total relevant cost of the system is minimized. We suggested a heuristic technique for solving the model. In broad terms, our solution technique combines a heuristic method for determining which candidate DCs to open and an exact method for minimizing costs given a set of open DCs. And we also developed a decision supporting package for the design of a physical distribution system.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.3
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• pp.277-284
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• 2013

To ensure that the production system of a factory is efficient, the factory layout design should consider the location and material flow plans of facilities, workshops, and storage areas. Highly productive factories need to have an optimized layout planning process, and a customized design methodology of the production system is a necessity for feasible layout planning. This paper presents a method for designing a layout module's size and shape and provides a heuristic location-allocation algorithm for the modules. The method is implemented and validated using a rich internet application-based platform. The layout design method is based on the leisure ship production process; this method can be used for designing the layout of a new factory or remodeling an existing factory and its production system. In contrast to existing layout methods, the inputs required for the proposed method, such as target products, production processes, and human-resource plans, are simple. This layout design method provides a useful solution for the initial stage of factory design.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.405-426
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• 2014

In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

• The Journal of Information Systems
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• v.28 no.4
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• pp.175-197
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• 2019

Purpose This study develops a heuristic algorithm to solve the time-resource tradeoffs in project scheduling problems with a real basis. Design/methodology/approach Resource constrained project scheduling problem with time-resource tradeoff is well-known as one of the NP-hard problems. Previous researchers have proposed heuristic that minimize Makespan of project scheduling by deriving optimal combinations from finite combinations of time and resource. We studied to solve project scheduling problems by deriving optimal values from infinite combinations. Findings We developed heuristic algorithm named Push Algorithm that derives optimal combinations from infinite combinations of time and resources. Developed heuristic algorithm based on simulated annealing shows better improved results than genetic algorithm and further research suggestion was discussed as a project scheduling problem with multiple resources of real numbers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.4
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• pp.94-101
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• 2005

This paper presents a data-mining aided heuristic algorithm development. The developed algorithm includes three steps. The steps are a uniform selection, development of feature functions and clustering, and a decision tree making. The developed algorithm is employed in designing an optimal multi-station fixture layout. The objective is to minimize the sensitivity function subject to geometric constraints. Its benefit is presented by a comparison with currently available optimization methods.

• Korean Management Science Review
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• v.25 no.1
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• pp.107-121
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• 2008

As to more efficiently manage the inventory in the retail supply chain and to meet the customer demand in a timely manner, vendor-managed inventory (VMI) has been widely accepted, which manages inventory in the retail supply chain via sharing information and collaborating with the retailers. Applying VMI generates vendor-managed inventory/distribution problem (VMIDP), which involves inventory management for both the vendor and the retailers, and the design of vehicle routes for delivery, to minimize the total operating cost in the supply chain. In this paper, we suggest a mixed integer programming (MIP) model to obtain the optimal solution for VMIDP in a two-echelon retail supply chain, and develop an efficient heuristic based on the operating principles of the MIP model. To evaluate the performance of the heuristic, its solution was compared with the one of the MIP model on a total of twenty seven test problems. As a result, the heuristic found optimal solutions on seven problems in a significantly reduced time, and generated a 4.3% error rate of total cost in average for all problems. The heuristic is applied to the case problem of the local famous franchise company together with GIS, showing that it is capable of providing a solution efficiently in a relatively short time even in the real world situation.