• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.150-153
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• 2001

The selection of the optimal partners in supply chain management is one of the most critical success factors. In the past, partners for outsourcing production were selected repeatedly within a closed group of candidates due to the limited information and location of partners. But, the wide use of internet and the development of electronic commerce make it possible that the partners capable of providing the optimal services are selected regardless of their location or nationality. And the concept of partners was limited to the provider of production resources. In the supply chain management, the concept should be extended to the provider of transportation and warehouse due to the high portion of transportation cost among the total production cost Therefore, In this study, we propose an analytical approach to the selection of Production and transportation partners in supply chain management. For this purpose a mathematical model is developed, and then a heuristic algorithm based on tabu search is presented since the model belongs to the NP hard problem.

• IE interfaces
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• v.21 no.3
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• pp.254-261
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• 2008

Connected-(r,s)-out of-(m,n) : F system is an important topic in redundancy design of the complex system reliability and it's maintenance policy. Previous studies applied Monte Carlo simulation and genetic, simulated annealing algorithms to tackle the difficulty of maintenance policy problem. These algorithms suggested most suitable maintenance cycle to optimize maintenance pattern of connected-(r,s)-out of-(m,n) : F system. However, genetic algorithm is required long execution time relatively and simulated annealing has improved computational time but rather poor solutions. In this paper, we propose the ant colony optimization approach for connected-(r,s)-out of-(m,n) : F system that determines maintenance cycle and minimum unit cost. Computational results prove that ant colony optimization algorithm is superior to genetic algorithm, simulated annealing and tabu search in both execution time and quality of solution.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.2
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• pp.1-10
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• 2000

With every passing month a number of new virtual enterprises emerge on the internet. Many companies have responded to the idea of distributed manufacturing in which the value adding activities comprising a finished product are dispersed geographically in a remote place. This study suggests an idea for selecting suppliers in a distributed manufacturing environment which enables machining companies to share their capacities. A mathematical model is constructed to show how to minimize the sum of the operation and transportation costs based on alternative process plans considering several kinds of operation characteristics in the real world. Four heuristic algorithms are developed to get an optimal or near-optimal solution using tabu search since the model is proven NP-hard. Example problems are tested to illustrate their procedure and performance.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.559-569
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• 1998

Cellular manufacturing system (CMS) has been recognized as an alternative to improve manufacturing productivity in conventional batch-type manufacturing systems through reducing set-up times, work-in-process inventories and throughput times by means of group technology. Most of the studies on the design of CMS assumed that each part has a unique process plan, and that its demand is known as a deterministic value despite of the probabilistic nature of the real world problems. This study suggests an approach for designing CMS, considering both alternative process plans and uncertain demand. A mathematical model is presented to show how to minimize the expected amortized and operating costs satisfying these two relaxations. Four heuristic algorithms are developed based on tabu search which is well suited for getting an optimal or near-optimal solution. Example problems are carried out to illustrate the heuristic algorithms and each of them is compared with the deterministic counterpart.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.117-133
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• 2011

In this paper, we present a frequency reassignment problem (FRP) arising from the reconfiguration of radio networks such as adding new base stations (BSs) and changing the number of frequencies assigned to BSs. For this problem, we develop an integer programming (IP) model that minimizes the sum of frequency reassignment cost and the cost for unsatisfied frequency demands, while avoiding interference among frequencies. To obtain tight lower bounds, we develop some valid inequalities and devise an objective function relaxation scheme. Also, we develop a simple but efficient heuristic procedure to solve large size problems. Computational results show that the developed valid inequalities are effective for improving lower bounds. Also, the proposed tabu search heuristic finds tight upper bounds with average optimality gap of 2.3%.

• IE interfaces
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• v.20 no.2
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• pp.103-111
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• 2007

A heterogeneous VRP which considers various capacities, fixed and variable costs was suggested in this study. The transportation cost for vehicle is composed of its fixed and variable costs incurred proportionately to the travel distance. The main objective is to minimize the total sum of transportation costs. A mathematical programming model was suggested for this purpose and it gives an optimal solution by using OPL-STUDIO (ILOG CPLEX). A genetic algorithm which considers improvement of an initial solution, new fitness function with weighted cost and distance rates, and flexible mutation rate for escaping local solution was also suggested. The suggested algorithm was compared with the results of a tabu search and sweeping method by Taillard and Lee, respectively. The suggested algorithm gives better solutions rather than existing algorithms.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.241-249
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• 1998

In this paper, we seek to find an optimal allocation of link capacity in a data communication network. The architecture of the data communication network considered in the study is an online-service network based on public switched telephone network(PSTN) and packet switched data network(PSDN). In designing the architecture of the network, we need to deal with various measures of quality of service(QoS). Two important service measures are the call blocking probability in PSTN and the data transfer delay time in PSDN. Considering the tradeoff between the call blocking probability and the data transfer delay time in the network, we have developed the optimal link capacity allocation model that minimizes the total link cost, while guarantees the call blocking probability and the data transfer delay time within an acceptable level of QoS. This problem can be formulated as a non-linear integer programming model. We have solved the problem with tabu search and simulated annealing methods. In addition, we have analyzed the sensitivity of the model and provided the insight of the model along with computational results.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.383-397
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• 2014

Reverse logistics network design issues have been popularly discussed in recent years. However, few papers in the past literature have been dedicated to incentive effect on return quantity of used products. The purpose of this study is to formulate a dynamic nonlinear programming model of reverse logistics network design with the aim of managing the used products allocation by coordinating the collection centers and recovery facilities to warrant economic efficiency. In the optimization model, a fuzzy approach is applied to interpret the relationship between the rate of return and the suggested incentives. Due to funding constraints in setting up the collection centers, this work considers these centers as multi-capacity levels, which can be opened or closed at different periods. In view of the fact that the problem is known as NP-hard, we propose a heuristic method based on tabu search procedure to solve the presented model. Finally, several dominance properties of optimal solutions are demonstrated in comparison with the results of a state-of-the-art commercial solver.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.329-343
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• 1995

Traditionally, machining process sequence was influenced and constrained by the design information obtained from CAD data base, i.e., class of operations, geometric shape, tooling, geometric tolerance, etc. However, even though all the constraints from design information are considered, there may exist more than one way to feasibly machine parts. This research is focused on the integrated problem of operations sequencing and machine tools selection in the presence of the product mix and their production volumes. With the transitional costs among machining operations, the operation sequencing problem can be formulated as a well-known Traveling Salesman Problem (TSP). The transitional cost between two operations is expressed as the sum of total machining time of the parts on a machine for the first operation and transportation time of the parts from the first machine to a machine for the second operation. Therefore, the operation sequencing problem formulated as TSP cannot be solved without transitional costs for all operation pairs. When solved separately or serially, their mutual optima cannot be guaranteed. Machining operations sequencing and machine tool selection problems are two core problems in process planning for discretely machined parts. In this paper, the interrelated two problems are integrated and analyzed, zero-one integer programming model for the integrated problem is formulated, and the solution methods are developed using a Tabu Search technique.