• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.1-12
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• 1991

This paper studies an optimal algorithm for the Maximum Origin-Destination Flor Path (MODFP) in an acyclic transportation network. We define a Pseudo-Flow each are so that it can give an upper bound to the total flow of a given path. And using the K-th Shortest Path algorithm we obtain upper bound of MODF which is decreasing as the number of searched path grows. Computational Complexity of optimal algorithm is O(K + m) $n_{2}$), K being the total number of searched path. We proved that the problem complexity of finding MODFP in an acyclic network is NP-hard, showing that the-satisfiability problem can be polynomialy reduced to this problem. And we estimated the average of the number K as being (m/n)$^{1,08}$ Exp (0.00689gm) from the computational experiments.

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

• IE interfaces
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• v.25 no.2
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• pp.153-162
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• 2012

The reliability is defined as a probability that a system will operate properly for a specified period of time under the design operating conditions without failure and it has been considered as one of the major design parameters in the field of industries. Reliability-Redundancy Optimization Problem(RROP) involves selec tion of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. However, in practice both active and cold standby redundancies may be used within a particular system design. Therefore, a redundancy strategy(active, cold standby) for each subsystem in order to maximize system reliability is considered in this study. Due to the nature of RROP, i.e. NP-hard problem, A Parallel Particle Swarm Optimization(PPSO) algorithm is proposed to solve the mathematical programming model and it gives consistently better quality solutions than existing studies for benchmark problems.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.354-363
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• 2016

Due to uncertain environment, various parameters such as price, queuing length, warranty, and so on influence on inventory models. In this paper, an inventory-queuing-pricing problem with continuous review inventory control policy and batch arrival queuing approach, is presented. To best of our knowledge, (I) demand function is stochastic and price dependent; (II) due to the uncertainty in real-world situations, a fuzzy programming approach is applied. Therefore, the presented model with goal of maximizing total profit of system analyzes the price and order quantity decision variables. Since the proposed model belongs to NP-hard problems, Pareto-based approaches based on non-dominated ranking and sorting genetic algorithm are proposed and justified to solve the model. Several numerical illustrations are generated to demonstrate the model validity and algorithms performance. The results showed the applicability and robustness of the proposed soft-computing-based approaches to analyze the problem.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.501-514
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• 1999

Multiple U-typed production lines are increasingly accepted in modern manufacturing system for the flexibility to adjust to changes in demand. This paper considers multiple U line balancing with the objective of minimizing cycle time considering of moving time of workforce given the number of workstation. Like the traditional line balancing problem this problem is NP-hard. In this paper, we show how genetic algorithm can be used to solve multiple U line balancing. For this, an encoding and a decoding method suitable to the problem are presented. Proper genetic operators are also employed. Extensive computational experiments are carried out to show the performance of the proposed algorithm. The computational results show that the algorithm is promising in solution quality.

• IE interfaces
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• v.14 no.2
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• pp.140-147
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• 2001

In the turbine-blade manufacturing industry, turbine-blades are machined and then are assembled to form a circular roll of blades. The roll of blades should be balanced as much as possible, since otherwise the efficiency of the turbine generator might be damaged. A locking blade is a blade whose location is fixed and a non-locking blade is a blade whose location can be freely changed. In this paper, we study methods for balancing the weights of the rotating blades for a turbine where some blades are locking blades. The turbine-blade balancing problem is formulated into a mixed-integer programming problem, which turns out to be NP-hard. A heuristic method based on the number partitioning algorithm is developed and the computational experiments show very promising results.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.10-18
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• 2002

A more comprehensive analytical framework for examining the relative merits of alternative dispatching process policies for nurseries is developed in this paper. The efficiency of the dispatch process of plants in a nursery is analysed using a vehicle routing model. The problem then involves determining in what order each vehicle should visit its locations. The problem is NP-hard. Several heuristic techniques are used to solve a real life nursery sequencing problem. The results obtained by these heuristic techniques are compared with each other and the current sequencing of orders. The model with some minor alterations can be also used to minimise the dispatching and collecting process in different agricultural plants.

• IE interfaces
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• v.13 no.4
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• pp.556-563
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• 2000

In this paper, we consider wavelength assignment problem (WAP) in Wavelength division multiplexed (WDM) unidirectional optical telecommunication ring networks. We show that, even though WAP on unidirectional ring belongs to NP-hard, WAP can be exactly solvable in real-sized WDM rings for near future demand. To accomplish this, we convert WAP to the vertex coloring problem of the related graph and choose a special integer programming formulation for the vertex coloring problem. We use a column generation technique in a branch-and-price framework for the suggested formulation. We also propose some generic heuristics and do the performance comparison with the suggested optimization algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.490-499
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• 1999

Vehicle routing problem(VRP) is known to be NP-hard problem, and good heuristic algorithm needs to be developed. To develop a heuristic algorithm for the VRP, this study suggests a parallel genetic algorithm(PGA), which determines each vehicle route in order to minimize the transportation costs. The PGA developed in this study uses two dimensional array chromosomes, which rows represent each vehicle route. The PGA uses new genetic operators. New mutation operator is composed of internal and external operators. internal mutation swaps customer locations within a vehicle routing, and external mutation swaps customer locations between vehicles. Ten problems were solved using this algorithm and showed good results in a relatively short time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.16-22
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• 2019

After Dantzig and Rasmer introduced Vehicle Routing Problem in 1959, this field has been studied with numerous approaches so far. Classical Vehicle Routing Problem can be described as a problem of multiple number of homogeneous vehicles sharing a same starting node and having their own routes to meet the needs of demand nodes. After satisfying all the needs, they go back to the starting node. In order to apply the real world problem, this problem had been developed with additional constraints and pick up & delivery model is one of them. To enhance the effectiveness of pick up & delivery, hub became a popular concept, which often helps reducing the overall cost and improving the quality of service. Lots of studies have suggested heuristic methods to realize this problem because it often becomes a NP-hard problem. However, because of this characteristic, there are not many studies solving this problem optimally. If the problem can be solved in polynomial time, optimal solution is the best option. Therefore, this study proposes a new mathematical model to solve this problem optimally, verified by a real world problem. The main improvements of this study compared to real world case are firstly, make drivers visit every nodes once except hub, secondly, make drivers visit every nodes at the right time, and thirdly, make drivers start and end their journey at their own homes.