• Kyungpook Mathematical Journal
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• v.57 no.4
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• pp.701-709
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• 2017

In this paper, we introduce the minimum covering Randic energy of a graph. We compute minimum covering Randic energy of some standard graphs and establish upper and lower bounds for this energy. Also we disprove a conjecture on Randic energy which is proposed by S. Alikhani and N. Ghanbari, [2].

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.1-11
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• 2010

The conditional covering problem is an important variation of well studied set covering problem. In the set covering problem, the problem is to find a minimum cardinality vertex set which will cover all the given demand points. The conditional covering problem asks to find a minimum cardinality vertex set that will cover not only the given demand points but also one another. This problem is NP-complete for general graphs. In this paper, we present an efficient algorithm to solve the conditional covering problem on interval graphs with n vertices which runs in O(n)time.

• Journal of applied mathematics & informatics
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• v.22 no.1_2
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• pp.435-440
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• 2006

Let G be a simple graph with vertex set V(G) and edge set E(G). A subset S of E(G) is called an edge cover of G if the subgraph induced by S is a spanning subgraph of G. The maximum number of edge covers which form a partition of E(G) is called edge covering chromatic number of G, denoted by X'c(G). It is known that for any graph G with minimum degree ${\delta},\;{\delta}-1{\le}X'c(G){\le}{\delta}$. If $X'c(G) ={\delta}$, then G is called a graph of CI class, otherwise G is called a graph of CII class. It is easy to prove that the problem of deciding whether a given graph is of CI class or CII class is NP-complete. In this paper, we consider the classification of nearly bipartite graph and give some sufficient conditions for a nearly bipartite graph to be of CI class.

• Journal of the Korean Operations Research and Management Science Society
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• v.15 no.2
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• pp.97-104
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• 1990

The problem is a variation of the weighted set-covering problem (SCP) which requires the minimum-cost cover to be self-covering. It is shown that direct extension of the well-known greedy heuristic for SCP can have an arbitrarily large error in the worst case. It remains an open question whther these exists a greedy heuristic with a finite error bound.

• Journal of the Korean Mathematical Society
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• v.46 no.4
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• pp.759-773
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• 2009

A dominating set for a graph G is a set D of vertices of G such that every vertex of G not in D is adjacent to a vertex of D. Reed [11] considered the domination problem for graphs with minimum degree at least three. He showed that any graph G of minimum degree at least three contains a dominating set D of size at most $\frac{3}{8}$ |V (G)| by introducing a covering by vertex disjoint paths. In this paper, by using this technique, we show that every graph on n vertices of minimum degree at least four contains a dominating set D of size at most $\frac{4}{11}$ |V (G)|.

• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.151-156
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• 2012

The current study presents a zero-one integer programming approach to determine the minimum break point set for the coordination of directional relays. First, the network is reduced if there are any parallel lines or three-end nodes. Second, all the directed loops are enumerated to reduce the iteration. Finally, the problem is formulated as a set-covering problem, and the break point set is determined using the zero-one integer programming technique. Arbitrary starting relay locations and the arbitrary consideration of relay sequence to set and coordinate relays result in navigating the loops many times and futile attempts to achieve system-wide relay coordination. These algorithms are compared with the existing methods, and the results are presented. The problem is formulated as a setcovering problem solved by the zero-one integer programming approach using LINGO 12, an optimization modeling software.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.384-391
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• 2000

Most of the previous works on classical location models are based on the assumption that the value(or utilities) of inventory remains constants over time. In this study a special case of location problem is studied for both ameliorating and deteriorating items in two-echelon supply-chain management such as agricultural and fishery products. The objective of this study is to determine the minimum number of storage facilities among a discrete set of location sites so that the probability for each customer to be covered is not less than a critical value. We have formulated this problem using stochastic set-covering problem which can be solved by 0-1 programming method. Also we developed a computer program and applied to a set of problems for fish culture storage and distribution centers and the sample results well show the impact of ameliorating and deteriorating rate on the location problem. For the further study, a graphical user-interface with visualization for input and output is needed to be developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.613-616
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• 2000

This paper considers the problem of subway crew scheduling. Crew scheduling is concerned with finding a minimum number of assignments of crews to a given timetable satisfying various restrictions. Traditionally, crew scheduling problem has been formulated as a set covering or set partitioning problem possessing exponentially many variables, but even the LP relaxation of the problem is hard to solve due to the exponential number of variables. In this paper, we propose two basic techniques that solve the problem in a reasonable time, though the optimality of the solution is not guaranteed. To reduce the number of variables, we adopt column-generation technique. We could develop an algorithm that solves column-generation problem in polynomial time. In addition, the integrality of the solution is accomplished by variable-fixing technique. Computational results show column-generation makes the problem of treatable size, and variable fixing enables us to solve LP relaxation in shorter time without a considerable increase in the optimal value. Finally, we were able to obtain an integer optimal solution of a real instance within a reasonable time.

• Korean Management Science Review
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• v.19 no.2
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• pp.75-89
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• 2002

According to the fast-paced environment of information technology and improving customer services, the design activities of logistics systems improve customer centric services and delivery performance implementing e-logistics system. The fundamental design issues that arise in the delivery system planning are optimizing the system with minimum cost and maximum throughput and service level. This study is concerned with the integrated model development of delivery system with customer responsive service level for DCM, Demand Chain Management. We used a two-step approach for this study. First, we formulated the supply. center facility planning using stochastic set-covering problem and assigned the customers to the supply center using clustering algorithm. Second, we developed vehicle delivery planning for a supply center based on GIS, GIS-VRP. Also we developed a GUI-type computer program for proposed method for supply center problem using GIS and Geo-DataBase of Busan area. The computational results showed that the proposed method was very effective on a set of test problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.67-86
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• 2002

This paper considers subway crew scheduling problem. Crew scheduling is concerned with finding a minimum number of assignments of crews to a given timetable satisfying various restrictions. Traditionally, crew scheduling problem has been formulated as a set covering or set partitioning problem possessing exponentially many variables, but even the LP relaxation of the problem is hard to solve due to the exponential number of variables. In this paper. we propose two basic techniques that solve the subway crew scheduling problem in a reasonable time, though the optimality of the solution is not guaranteed. We develop an algorithm that solves the column-generation problem in polynomial time. In addition, the integrality of the solution is accomplished by variable-fixing technique. Computational result for a real instance is reported.