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

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1994.04a
• /
• pp.236-243
• /
• 1994

In this paper we consider the part-machine cell formation decision of the generalized Group Technology(GT) problem in which multiple process routes can be generated for each part. The existing p-median model and similarity coefficient algorithm can solve only small-sized or well-structured cases. We suggest an assignment method for the cell formation problem. This method uses an assignment model which is a simple linear programming. Numerical examples show that our assignment method provides good separable cells formation even for large-sized and ill-structured problems.

• Journal of Korean Institute of Industrial Engineers
• /
• v.14 no.2
• /
• pp.41-51
• /
• 1988

In this paper an efficient heuristic for the generalized assignment problem(GAP) is presented. A new lower bound that is slightly improved by adding the feasibility constraint is used to measure the quality of solutions obtained by the heuristic. The heuristic was tested on a number of large-scale random problems and a large sample of small problems. The heuristic appears to be better than the best previously existing heuristic for GAP. Its effectiveness in comparison of running times and closenesses to lower bound is discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1995.04a
• /
• pp.47-53
• /
• 1995

The Generalized Assignment (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.

• IE interfaces
• /
• v.22 no.3
• /
• pp.263-277
• /
• 2009

This research deals with a task assignment problem to worker group which consists of one master and one assistant. Each task must be assigned to only one worker group and it is possible to make a pair of each master and each assistant to organize a worker group. A worker group may have more than one task assigned to it, but the workloads of each worker group must be balanced within the allowable range. This problem can be formulated mathematically using the Mixed Integer Programming(MIP), where the objective function is to minimize the total assignment cost. A two phase heuristic algorithm is suggested in order to find approximate solutions. The first phase is to obtain an initial solution, where the initial assignment is performed to follow the workload adjustment. In the second phase, the solution is improved through the repeated process of the exchange and the assignment adjustment. Numerical experiments have been performed to evaluate the performance of the heuristic algorithm.

• International Journal of Control, Automation, and Systems
• /
• v.3 no.2
• /
• pp.159-165
• /
• 2005

This paper designs observers for matrix second-order linear systems on the basis of generalized eigenstructure assignment via unified parametric approach. It is shown that the problem is closely related with a type of so-called generalized matrix second-order Sylvester matrix equations. Through establishing two general parametric solutions to this type of matrix equations, two unified complete parametric methods for the proposed observer design problem are presented. Both methods give simple complete parametric expressions for the observer gain matrices. The first one mainly depends on a series of singular value decompositions, and is thus numerically simple and reliable; the second one utilizes the right factorization of the system, and allows eigenvalues of the error system to be set undetermined and sought via certain optimization procedures. A spring-mass system is utilized to show the effect of the proposed approaches.

• Journal of Communications and Networks
• /
• v.18 no.6
• /
• pp.884-891
• /
• 2016

The wireless mesh network (WMN) has attracted significant interests as a broadband wireless network to provide ubiquitous wireless access for broadband services. Especially with incorporating multiple orthogonal channels and multiple directional antennas into the WMN, each node can communicate with its neighbor nodes simultaneously without interference between them. However, as we allow more freedom, we need a more sophisticated algorithm to fully utilize it and developing such an algorithm is not easy in general. In this paper, we study a joint channel assignment, link scheduling, routing, and rate control problem for the WMN with multiple orthogonal channels and multiple directional antennas. This problem is inherently hard to solve, since the problem is formulated as a mixed integer nonlinear problem (MINLP). However, despite of its inherent difficulty, we develop an algorithm to solve the problem by using the generalized Benders decomposition approach [2]. The simulation results show the proposed algorithm provides the optimal solution to maximize the network utility, which is defined as the sum of utilities of all sessions.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.636-638
• /
• 1997

This paper deals with the problem of finding robust controller based upon a pole assignment method for a plant with parameter perturbations. This case is not a problem of Interval polynomial family but a problem of poly topic polynomial family. As a method of stability test, we used GKT(Generalized Kharitonov Theorem) having computational advantage.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.5
• /
• pp.151-158
• /
• 2023

The researchers entirely focused on meta-heuristic method for generalized assignment problem(GAP) that is known as NP-hard problem because of the optimal solution within polynomial time algorithm is unknown yet. On the other hand, this paper proposes a heuristic greedy algorithm with rules for finding solutions. Firstly, this paper reduces the weight matrix of original data to w_ij ≤ b_i/l in order to n jobs(items) pack m machines(bins) with l = n/m. The maximum profit of each job was assigned to the machine for the reduced data. Secondly, the allocation was adjusted so that the sum of the weights assigned to each machine did not exceed the machine capacity. Finally, the k-opt swap optimization was performed to maximize the profit. The proposed algorithm is applied to 50 benchmarking data, and the best known solution for about 1/3 data is to solve the problem. The remaining 2/3 data showed comparable results to metaheuristic techniques. Therefore, the proposed algorithm shows the possibility that rules for finding solutions in polynomial time exist for GAP. Experiments demonstrate that it can be a P-problem from an NP-hard.