Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Industrial Engineering and Management Systems
Journal Basic Information
Journal DOI :
Korean Institute of Industrial Engineers
Editor in Chief :
Volume & Issues
Volume 12, Issue 4 - Dec 2013
Volume 12, Issue 3 - Sep 2013
Volume 12, Issue 2 - Jun 2013
Volume 12, Issue 1 - Mar 2013
Selecting the target year
Foreword-Special Issue on Metaheuristic Application and Operations Management
Luong, Huynh Trung ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 171~171
DOI : 10.7232/iems.2013.12.3.171
Genetic Algorithm-Based Coordinated Replenishment in Multi-Item Inventory Control
Nagasawa, Keisuke ; Irohara, Takashi ; Matoba, Yosuke ; Liu, Shuling ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 172~180
DOI : 10.7232/iems.2013.12.3.172
We herein consider a stochastic multi-item inventory management problem in which a warehouse sells multiple items with stochastic demand and periodic replenishment from a supplier. Inventory management requires the timing and amounts of orders to be determined. For inventory replenishment, trucks of finite capacity are available. Most inventory management models consider either a single item or assume that multiple items are ordered independently, and whether there is sufficient space in trucks. The order cost is commonly calculated based on the number of carriers and the usage fees of carriers. In this situation, we can reduce future shipments by supplementing items to an order, even if the item is not scheduled to be ordered. On the other hand, we can reduce the average number of items in storage by reducing the order volume and at the risk of running out of stock. The primary variables of interest in the present research are the average number of items in storage, the stock-out volume, and the number of carriers used. We formulate this problem as a multi-objective optimization problem. In a numerical experiment based on actual shipment data, we consider the item shipping characteristics and simulate the warehouse replenishing items coordinately. The results of the simulation indicate that applying a conventional ordering policy individually will not provide effective inventory management.
Two-Phase Genetic Algorithm for Solving the Paired Single Row Facility Layout Problem
Parwananta, Hutama ; Maghfiroh, Meilinda F.N. ; Yu, Vincent F. ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 181~189
DOI : 10.7232/iems.2013.12.3.181
This paper proposes a two-phase genetic algorithm (GA) to solve the problem of obtaining an optimum configuration of a paired single row assembly line. We pair two single-row assembly lines due to the shared usage of several workstations, thus obtaining an optimum configuration by considering the material flow of the two rows simultaneously. The problem deals with assigning workstations to a sequence and selecting the best arrangement by looking at the length and width for each workstation. This can be considered as an enhancement of the single row facility layout problem (SRFLP), or the so-called paired SRFLP (PSRFLP). The objective of this PSRFLP is to find an optimal configuration that seeks to minimize the distance traveled by the material handler and even the use of the material handler itself if this is possible. Real-world applications of such a problem can be found for apparel, shoe, and other manual assembly lines. This research produces the schematic representation solution using the heuristic approach. The crossover and mutation will be utilized using the schematic representation solution to obtain the neighborhood solutions. The first phase of the GA result is recorded to get the best pair. Based on these best matched pairs, the second-phase GA can commence.
Capacitated Location and Allocation Models of Long-Term Care Facilities
Song, Byung Duk ; Ko, Young Dae ; Morrison, James R. ; Hwang, Hark ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 190~197
DOI : 10.7232/iems.2013.12.3.190
People are living longer than ever before. As a result, life expectancy is going up and the demand of long-term care facilities is increasing in most countries. The facilities provide rehabilitative, restorative, and skilled nursing care to patients or residents in need of assistance with activities of daily living. This study deals with the capacitated location and allocation problem of long-term care facilities in a city that consists of a finite number of regions. Assuming that in each region candidate locations for three types of facilities are already given, two integer programming models are developed under the closest assignment rule reflecting the demand characteristics of the facilities. Both the location and type of the facilities to be built become decision variables. To show the validity of the models, numerical problems are solved with commercial software, CPLEX. Also, sensitivity studies were conducted to identify relationships between the system parameters.
Solving the Team Orienteering Problem with Particle Swarm Optimization
Ai, The Jin ; Pribadi, Jeffry Setyawan ; Ariyono, Vincensius ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 198~206
DOI : 10.7232/iems.2013.12.3.198
The team orienteering problem (TOP) or the multiple tour maximum collection problem can be considered as a generic model that can be applied to a number of challenging applications in logistics, tourism, and other fields. This problem is generally defined as the problem of determining P paths, in which the traveling time of each path is limited by
that maximizes the total collected score. In the TOP, a set of N vertices i is given, each with a score
. The starting point (vertex 1) and the end point (vertex N) of all paths are fixed. The time
needed to travel from vertex i to j is known for all vertices. Some exact and heuristics approaches had been proposed in the past for solving the TOP. This paper proposes a new solution methodology for solving the TOP using the particle swarm optimization, especially by proposing a solution representation and its decoding method. The performance of the proposed algorithm is then evaluated using several benchmark datasets for the TOP. The computational results show that the proposed algorithm using specific settings is capable of finding good solution for the corresponding TOP instance.
Mathematical Model for Revenue Management with Overbooking and Costly Price Adjustment for Hotel Industries
Masruroh, Nur Aini ; Mulyani, Yun Prihantina ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 207~223
DOI : 10.7232/iems.2013.12.3.207
Revenue management (RM) has been widely used to model products characterized as perishable. Classical RM model assumed that price is the sole factor in the model. Thus price adjustment becomes a crucial and costly factor in business. In this paper, an optimal pricing model is developed based on minimization of soft customer cost, one kind of price adjustment cost and is solved by Lagrange multiplier method. It is formed by expected discounted revenue/bid price integrating quantity-based RM and pricing-based RM. Quantity-based RM consists of two capacity models, namely, booking limit and overbooking. Booking limit, built by assuming uncertain customer arrival, decides the optimal capacity allocation for two market segments. Overbooking determines the level of accepted order exceeding capacity to anticipate probability of cancellation. Furthermore, pricing-based RM models occupancy/demand rate influenced by internal and competitor price changes. In this paper, a mathematical model based on game theoretic approach is developed for two conditions of deterministic and stochastic demand. Based on the equilibrium point, the best strategy for both hotels can be determined.
Development of a Composite Revenue Sharing-Quantity Flexibility Contract
Lumsakul, Pasuree ; Luong, Huynh Trung ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 224~233
DOI : 10.7232/iems.2013.12.3.224
In supply chain management, the supply contract can induce collaboration and coordination among the supply chain members in order to optimize supply chain performance. Numerous supply contracts have been examined; however, some difficulties related to the application of these contracts still occur. One of the solutions is to apply the composite supply contract which can assist in the supply chain coordination. This research examines the composite contract of the revenue sharing and quantity flexibility contracts in a two-stage supply chain, which comprises a retailer and a supplier. In this research, a mathematical model of the composite contract is developed; then, the applicability of the proposed composite contract is examined by investigating its capability in terms of supply chain coordination and profit allocation. In the numerical experiments, the composite revenue sharing-quantity flexibility contract showed that it is superior to both component contracts in terms of supply chain coordination and profit allocation among supply chain members.
Design of Personal Spiral Conjoint Analysis
Castel, Dennis ; Saga, Ryosuke ; Tsuji, Hiroshi ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 234~243
DOI : 10.7232/iems.2013.12.3.234
In order to point out the best utility of a product (or a service), marketers need to clearly understand and measure the preference of the consumers. Among numerous marketing analysis techniques, the conjoint analysis is one of the popular tools for market research. One of the issues with this tool is the lack of feedback for the respondents. This paper proposes personal stepwise conjoint analysis based on an interactive Web-questionnaire allowing respondents to receive a diagnosis of their evaluation and giving the possibility to reconsider their evaluation. To validate our proposal, experimentation with forty-two respondents is also demonstrated. Experimental results, potential modifications and improvements are detailed in this paper.
A Hybrid Method to Improve Forecasting Accuracy Utilizing Genetic Algorithm: An Application to the Data of Processed Cooked Rice
Takeyasu, Hiromasa ; Higuchi, Yuki ; Takeyasu, Kazuhiro ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 244~253
DOI : 10.7232/iems.2013.12.3.244
In industries, shipping is an important issue in improving the forecasting accuracy of sales. This paper introduces a hybrid method and plural methods are compared. Focusing the equation of exponential smoothing method (ESM) that is equivalent to (1, 1) order autoregressive-moving-average (ARMA) model equation, a new method of estimating the smoothing constant in ESM had been proposed previously by us which satisfies minimum variance of forecasting error. Generally, the smoothing constant is selected arbitrarily. However, this paper utilizes the above stated theoretical solution. Firstly, we make estimation of ARMA model parameter and then estimate the smoothing constant. Thus, theoretical solution is derived in a simple way and it may be utilized in various fields. Furthermore, combining the trend removing method with this method, we aim to improve forecasting accuracy. This method is executed in the following method. Trend removing by the combination of linear and 2nd order nonlinear function and 3rd order nonlinear function is executed to the original production data of two kinds of bread. Genetic algorithm is utilized to search the optimal weight for the weighting parameters of linear and nonlinear function. For comparison, the monthly trend is removed after that. Theoretical solution of smoothing constant of ESM is calculated for both of the monthly trend removing data and the non-monthly trend removing data. Then forecasting is executed on these data. The new method shows that it is useful for the time series that has various trend characteristics and has rather strong seasonal trend. The effectiveness of this method should be examined in various cases.
A PROMETHEE Method Based Heuristic for Disassembly Line Balancing Problem
Avikal, Shwetank ; Mishra, P.K. ; Jain, Rajeev ; Yadav, H.C. ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 254~263
DOI : 10.7232/iems.2013.12.3.254
Disassembly of discarded products takes place in the process of remanufacturing, recycling, and disposal. The disassembly lines have been taken as available choice for automated disassembly; therefore, it has become essential that it be designed and balanced to work efficiently. The multi-objective disassembly line balancing problem seeks to find a disassembly sequence which provides a feasible disassembly sequence, minimizes the number of workstations and idle time, and balances the line for the disassembly of post consumed product by considering the environment effects. This paper proposes a multi-criteria decision making technique based heuristic for assigning the disassembly tasks to the workstations. In the proposed heuristic, the PROMETHEE method is used for prioritizing the tasks to be assigned. The tasks are assigned to the disassembly workstations according to their priority rank and precedence relations. The proposed heuristic is illustrated with an example, and the results show that substantial improvement in the performance is achieved compared with other heuristics.
Asymmetric Information Supply Chain Models with Credit Option
Zhang, Xu ; Zeephongsekul, Panlop ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 264~273
DOI : 10.7232/iems.2013.12.3.264
Credit option is a policy that has been studied by many researchers in the area of supply chain management. This policy has been applied in practice to improve the profits of supply chain members. Usually, a credit option policy is proposed by the seller, and often under a symmetric information environment where members have complete information on each others` operations. In this paper, we investigate two scenarios: firstly, the seller offers a credit option to the buyer, and secondly, the buyer attempts to stretch the length of the credit period offered by the seller. The proposed model in both scenarios will be investigated under an asymmetric information structure where some information are private and are only known to the individual who has knowledge of this information. The interactions between buyer and seller will be modeled by non-cooperative Stackelberg games where the buyer and seller take turn as leader and follower. Among some of the numerical results obtained, the seller and buyer`s profits obtained from symmetric information games are larger than those obtained from an asymmetric information game in both scenarios. Furthermore, both buyer and seller`s profit in the second scenario are better than in the first scenario.
A Space Merging Approach to the Analysis of the Performance of Queueing Models with Finite Buffers and Priority Jumps
Oh, Youngjin ; Kim, Chesoong ; Melikov, Agassi ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 274~280
DOI : 10.7232/iems.2013.12.3.274
This paper proposes a space merging approach to studying the queuing models with finite buffers and jump priorities. Upon the arrival of a call with low priority, one call of such kind is assumed to be transferred to the end of the queue of high priority calls. The transfer probabilities depend on the state of the queue of the heterogeneous calls. We developed the algorithms to calculate the quality of service metrics of such queuing models, and the results of the numerical experiments are shown.
A Roots Method in GI/PH/1 Queueing Model and Its Application
Choi, Kyung Hwan ; Yoon, Bong Kyoo ;
Industrial Engineering and Management Systems, volume 12, issue 3, 2013, Pages 281~287
DOI : 10.7232/iems.2013.12.3.281
In this paper, we introduce a roots method that uses the roots inside the unit circle of the associated characteristics equation to evaluate the steady-state system-length distribution at three epochs (pre-arrival, arbitrary, and post-departure) and sojourn-time distribution in GI/PH/1 queueing model. It is very important for an air base to inspect airplane oil because low-quality oil leads to drop or breakdown of an airplane. Since airplane oil inspection is composed of several inspection steps, it sometimes causes train congestion and delay of inventory replenishments. We analyzed interarrival time and inspection (service) time of oil supply from the actual data which is given from one of the ROKAF`s (Republic of Korea Air Force) bases. We found that interarrival time of oil follows a normal distribution with a small deviation, and the service time follows phase-type distribution, which was first introduced by Neuts to deal with the shortfalls of exponential distributions. Finally, we applied the GI/PH/1 queueing model to the oil train congestion problem and analyzed the distributions of the number of customers (oil trains) in the queue and their mean sojourn-time using the roots method suggested by Chaudhry for the model GI/C-MSP/1.