• Journal of Korean Institute of Industrial Engineers
• /
• v.19 no.2
• /
• pp.105-117
• /
• 1993

Methods for calculating k shortest paths in a network system, are based on a analogy which exists between the solution of a network problem and traditional techniques for solving linear equations. This paper modifies an algebraic structure of the K shortest path method and develops k maximum flow methods. On the basis of both theoretical and algebraic structure, three iteration methods are developed and the effective procedure of each method are provided. Finally, computational complexity is discussed for those methods.

• Korean Management Science Review
• /
• v.7 no.2
• /
• pp.51-57
• /
• 1990

The purpose of this thesis is to find the shortest path between two nodes on an acyclic network where the arc costs are determined by the starting time at the starting node of the arc. A branch and bound method for optimal solutions and a heuristic method is developed. In heuristic method Dijkstra algorithm is modified to maintain the minimum arrival times of maximum informations in the each time period at each node and is updated by the result with the insertion technique. Expermetal results among two methods are presented with regard to run time and solution qualities.

• Journal of Korea Society of Industrial Information Systems
• /
• v.8 no.3
• /
• pp.91-98
• /
• 2003

Visitors who browse the web from wireless PDAs, cell phones are frequently frustrated by interfaces. Simply replacing graphics with text and reformatting tables does not solve this problem, because deep link structures can still require more time. To solve this problem, in the paper we propose an algorithm, Minimal Path Algorithm that automatically improves wireless web navigation by suggesting useful shortcut links in real time. In the result of this paper, Minimal Path algorithm offer the shortcut and the number of shortest links to web users.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.3
• /
• pp.31-41
• /
• 1995

The maximum Origin-Destination Flow Path Problem (MODFP) in an Acyclic Network has known as NP-hard. K. S. Sung has suggested on Optimal Algorithm for MODFP based on the Pseudo flo or arc and the K-th shortest path algorithm. When we try to solve MODFP problem by general Branch and Bound Method (BBM), the upper and lower bounds of subproblems are so weak that the BBM become very inefficient. Here we utilized the Pseudo flow of arc' for the tight bounds of subproblems so that it can produce an efficient BBM for MODFP problem.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.23 no.61
• /
• pp.33-39
• /
• 2000

In this paper, we present an algorithm for the multicast routing problem when there exit the cell replication limits of ATM switching nodes. This problem can be formulated as a Degree Constrained Minimum Steiner Tree Problem(DCSP). The proposed algorithm is a modification of the shortest path heuristic originally devised for minimum Steiner tree problem. From the experimental results, it can be seen that our algorithm is efficient to obtain a near optimal solution with comparatively low computational time.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2004.10a
• /
• pp.225-228
• /
• 2004

The generalized knapsack problem, or gknap is the combinatorial optimization problem of optimizing a nonnegative linear functional over the integral hull of the intersection of a polynomially separable 0 - 1 polytope and a knapsack constraint. Among many potential applications, the knapsack, the restricted shortest path, and the restricted spanning tree problem are such examples. We prove via the ellipsoid method the equivalence between the fully polynomial approximability and a certain pseudo-polynomial separability of the gknap polytope.

• Journal of Internet Computing and Services
• /
• v.12 no.2
• /
• pp.47-53
• /
• 2011

When some sensors under Wireless Sensor Networks fail or become energy-exhausted, redundant mobile sensors might be moved to recover the sensing holes. Within rugged terrain where wheeled sensors are unsuitable, other type of mobile sensors, such as hopping sensors, are needed. In this paper, we address the problem of relocating hopping sensors to the detected sensing holes. Recent study for this work considered the relocation using the shortest path between clusters; however, the shortest path might be used repeatedly and create other sensing holes. In order to overcome the mentioned problem, we propose relocation schemes using the most disjointed paths or multi-paths. Simulation results show that the proposed schemes guarantee more balanced migration distributions of efficient sensors and higher movement success ratios of required sensors than those of the shortest path-based scheme.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.9
• /
• pp.81-86
• /
• 2015

This paper suggests heuristic algorithm with linear time complexity to decide the normal and optimal point at minimum loss/maximum profit maximum shortest scheduling problem with additional loss cost and bonus profit cost. This algorithm computes only the earliest ending time for each node. Therefore, this algorithm can be get the critical path and project duration within O(n) time complexity and reduces the five steps of critical path method to one step. The proposed algorithm can be show the result more visually than linear programming and critical path method. For real experimental data, the proposed algorithm obtains the same solution as linear programming more quickly.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.34 no.3
• /
• pp.24-34
• /
• 2011

An Unmanned Aerial Vehicle (UAV) is a powered pilotless aircraft, which is controlled remotely or autonomously. UAVs are an attractive alternative for many scientific and military organizations. UAVs can perform operations that are considered to be risky or uninhabitable for human. UA V s are currently employed in many military missions such as reconnaissance, surveillance, enemy radar jamming, decoying, suppression of enemy air defense (SEAD), fixed and moving target attack, and air-to-air combat. UAVs also are employed in a number of civilian applications such as monitoring ozone depletion, inclement weather, traffic congestion, and taking images of dangerous territory. For accomplishing the UAV's missions, guarantee of survivability should be preceded. The main objective of this study is to suggest a mathematical programming model and a $A^*PS$-PGA (A-star with Post Smoothing-Parallel Genetic Algorithm) for an UAV's path planning to maximize survivability. A mathematical programming model is composed by using MRPP (Most Reliable Path Problem) and TSP (Traveling Salesman Problem). A path planning algorithm for UAV is applied by transforming MRPP into SPP (Shortest Path Problem).

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2006.05a
• /
• pp.95-108
• /
• 2006

Because of rapid expansion of third party logistics, fierce competition in the transportation industry, and the diversification and globalization of transportation channels, an effective transportation planning by means of multimodal transport is badly needed. Accordingly, this study aims to suggest an optimal transport algorithm for the multimodal transport in the international logistics. Cargoes and stopovers can be changed numerously according to the change of transportation modes, thus being a NP-hard problem. As a solution for this problem, first of all, we have applied a pruning algorithm to simplify it, suggesting a heuristic algorithm for constrained shortest path problem to find out a feasible area with an effective time range and effective cost range, which has been applied to the Label Setting Algorithm, consequently leading to multiple Pareto optimal solutions. Also, in order to test the efficiency of the algorithm for constrained shortest path problem, this paper has applied it to the actual transportation path from Busan port of Korea to Rotterdam port of Netherlands.