International Journal of Advanced Operations Management http://www.inderscience.com/browse/index.php?journalID=340&year=2011&vol=3&issue=2 Inderscience Publishers Ltd en-uk International Journal of Advanced Operations Management 1758-938X 1758-9398 © 2011 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijaom_scoverijaom.jpg http://www.inderscience.com/browse/index.php?journalID=340&year=2011&vol=3&issue=2 http://www.inderscience.com/link.php?id=42135 In this study, a supply chain model consisting of a single product, one supplier and one retailer is considered. Transportation times are constant and demands at the retailer are assumed to be generated by a stationary Poisson process. Demands not covered immediately from inventory are backordered. The retailer carries inventory and replenishes stock according to a (Q, R) policy. The supplier has online information about the demand at the retailer and uses this information to replenish its stock. The order size at the supplier is a multiple integer to the retailer's order size. Considering order costs for the retailer and the supplier, we derive the exact cost function for this inventory system. Then, using a search method, the optimal solution for the exact value of the expected system costs is found. Furthermore, for utilising information in the supplier's decision making, we resort to solve several numerical examples. Shared information in a serial inventory system
Nima Yazdan Shenas, Abdolhamid Eshraghniaye Jahromi, Kourosh Eshghi
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 101 - 121
In this study, a supply chain model consisting of a single product, one supplier and one retailer is considered. Transportation times are constant and demands at the retailer are assumed to be generated by a stationary Poisson process. Demands not covered immediately from inventory are backordered. The retailer carries inventory and replenishes stock according to a (Q, R) policy. The supplier has online information about the demand at the retailer and uses this information to replenish its stock. The order size at the supplier is a multiple integer to the retailer's order size. Considering order costs for the retailer and the supplier, we derive the exact cost function for this inventory system. Then, using a search method, the optimal solution for the exact value of the expected system costs is found. Furthermore, for utilising information in the supplier's decision making, we resort to solve several numerical examples.

]]> 10.1504/IJAOM.2011.042135 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 101 - 121 Nima Yazdan Shenas Abdolhamid Eshraghniaye Jahromi Kourosh Eshghi Department of Industrial Engineering, University of Science and Culture, P.O. Box 13145-871, Tehran, Iran. ' Department of Industrial Engineering, Sharif University of Technology, P.O. Box 11365-9414, Tehran, Iran. ' Department of Industrial Engineering, Sharif University of Technology, P.O. Box 11365-9414, Tehran, Iran two-level inventory systems information exchange continuous review fixed order cost Poisson demand backordered demand different order sizes single products information sharing supply chain management SCM modelling. 2011-08-28T23:20:50-05:00 3 2 101 121 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42136 Many real world scheduling problems involve simultaneous optimisation of multiple objectives and the trade-off between the objectives is crucial. The present work is an attempt to address the multi-objective job shop scheduling using a hybrid differential evolution approach. The objectives considered in the study are minimisation of makespan, mean flow time and mean tardiness. The operation schedule is generated using random keys encoding scheme which deals with the floating point vectors. A local search heuristic is embedded in the algorithm to achieve the best optimal solution. The proposed approach is tested on various job shop scheduling instances reported in the literature and it is observed that the proposed approach is performing well on all the test problems. Multi-objective job shop scheduling using hybrid differential evolution approach
G. Balaraju, Sriram Venkatesh, B. Siva Prasad Reddy
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 122 - 140
Many real world scheduling problems involve simultaneous optimisation of multiple objectives and the trade-off between the objectives is crucial. The present work is an attempt to address the multi-objective job shop scheduling using a hybrid differential evolution approach. The objectives considered in the study are minimisation of makespan, mean flow time and mean tardiness. The operation schedule is generated using random keys encoding scheme which deals with the floating point vectors. A local search heuristic is embedded in the algorithm to achieve the best optimal solution. The proposed approach is tested on various job shop scheduling instances reported in the literature and it is observed that the proposed approach is performing well on all the test problems.

]]> 10.1504/IJAOM.2011.042136 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 122 - 140 G. Balaraju Sriram Venkatesh B. Siva Prasad Reddy Department of Mechanical Engineering, University College of Engineering, Osmania University, Hyderabad – 500007, Andhra Pradesh, India. ' Department of Mechanical Engineering, University College of Engineering, Osmania University, Hyderabad – 500007, Andhra Pradesh, India. ' Department of Mechanical Engineering, Kakatiya Institute of Technology & Science, Warangal – 506015, Andhra Pradesh, India job shop scheduling differential evolution random keys makespan Pareto front local search multiobjective scheduling mean flow time mean tardiness floating point vectors. 2011-08-28T23:20:50-05:00 3 2 122 140 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42137 We consider the problem of assigning job due-dates when the objective is to minimise the total expected earliness and tardiness penalty. This type of problem is important because modern production and distribution systems discourage both tardy and early deliveries. This paper extends a general due-date policy, the so-called SL rule, to incorporate not only tardiness but also earliness. We provide optimal policy parameters for the linear and quadratic penalty cases in an M/M/1 system. Job due-date assignment with earliness and tardiness penalties and stochastic arrival and service times
Xiaoming Li, V. Sridharan, John J. Kanet, Yifeng Zhang
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 141 - 152
We consider the problem of assigning job due-dates when the objective is to minimise the total expected earliness and tardiness penalty. This type of problem is important because modern production and distribution systems discourage both tardy and early deliveries. This paper extends a general due-date policy, the so-called SL rule, to incorporate not only tardiness but also earliness. We provide optimal policy parameters for the linear and quadratic penalty cases in an M/M/1 system.

]]> 10.1504/IJAOM.2011.042137 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 141 - 152 Xiaoming Li V. Sridharan John J. Kanet Yifeng Zhang Department of Business Administration, Tennessee State University, 330 10th Ave. N, Nashville, TN 37203, USA. ' Department of Management, Clemson University, 101C Sirrine Hall, Clemson, SC 29634, USA. ' Department of MIS, OM, and DSC, University of Dayton, 300 College Park, Dayton, OH 45469, USA. ' Department of Management Information Systems, University of Illinois at Springfield, One University Plaza, Springfield, IL 62703, USA scheduling due-date assignment earliness penalty tardiness penalty stochastic arrival times stochastic service times. 2011-08-28T23:20:50-05:00 3 2 141 152 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42138 From the published literature, it was found that there is a scope to develop models to select between preventive maintenance (PM) and breakdown maintenance (BDM) with optimal schedule. But an organisation using multiple criteria decides to embark PM with a value of its optimal schedule common to all the criteria chosen. To this effect, a system has been developed to determine collaborative schedule for an equipment taking into consideration of those three criteria. This system consists of three phases. Input phase using a developed and published method by the authors provides the information whether or not PM is preferable and optimal schedule for that criterion chosen. Criteria importance through inter-criteria correlation (CRITIC) method is used to evolve weights without subjectivity. Goal-programming has been used to derive a single common schedule for PM, in optimisation phase. The system was applied to cases and the analysis carried out is reported in the paper. Collaborative optimal preventive maintenance schedule using goal programming
V. Mariappan, A. Subash Babu, S. Rajasekaran, K. Ilayaraja
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 153 - 174
From the published literature, it was found that there is a scope to develop models to select between preventive maintenance (PM) and breakdown maintenance (BDM) with optimal schedule. But an organisation using multiple criteria decides to embark PM with a value of its optimal schedule common to all the criteria chosen. To this effect, a system has been developed to determine collaborative schedule for an equipment taking into consideration of those three criteria. This system consists of three phases. Input phase using a developed and published method by the authors provides the information whether or not PM is preferable and optimal schedule for that criterion chosen. Criteria importance through inter-criteria correlation (CRITIC) method is used to evolve weights without subjectivity. Goal-programming has been used to derive a single common schedule for PM, in optimisation phase. The system was applied to cases and the analysis carried out is reported in the paper.

]]> 10.1504/IJAOM.2011.042138 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 153 - 174 V. Mariappan A. Subash Babu S. Rajasekaran K. Ilayaraja Roever Engineering College, Perambalur, Tamilnadu 621212, India. ' IDP-Industrial Engineering and Operations Research, IIT Bombay, Mumbai-400 076, India. ' Department of Electrical and Electronics Engineering, Roever Engineering College, Perambalur, Tamilnadu 621212, India. ' Department of Mechanical Engineering, Roever Engineering College, Perambalur, Tamilnadu 621212, India collaborative scheduling CRITIC method goal programming optimisation preventive maintenance maintenance scheduling. 2011-08-28T23:20:50-05:00 3 2 153 174 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42139 This paper considers an organisation with a single server and single or bulk service characterised by the bilevel service discipline introduced by Baburaj (1999, pp.15-22). In this organisation, on one hand, if the queue size n is not more than a constant r then the server takes a single customer for service according to FCFS rule. On the other hand, if the size is more than r then he serves min{n, R}(R > r) units in a batch according to the same rule. While Baburaj assumes exponential service times we consider general service time distributions. The first objective is to derive the probability generating function of the number of customers in the system at a service completion epoch and at an arbitrary instant of time as well as the performance characteristics of the system. The second objective is to develop an optimal management policy, through a quick search algorithm, to obtain the optimal values of the parameters r and R which minimise a suitable cost structure. This model is useful in different real-world operational management problems to minimise the organisation costs while keeping a high customer satisfaction level. Optimal management policy for a single and bulk service queue
Lotfi Tadj, Chafik Abid
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 175 - 187
This paper considers an organisation with a single server and single or bulk service characterised by the bilevel service discipline introduced by Baburaj (1999, pp.15-22). In this organisation, on one hand, if the queue size n is not more than a constant r then the server takes a single customer for service according to FCFS rule. On the other hand, if the size is more than r then he serves min{n, R}(R > r) units in a batch according to the same rule. While Baburaj assumes exponential service times we consider general service time distributions. The first objective is to derive the probability generating function of the number of customers in the system at a service completion epoch and at an arbitrary instant of time as well as the performance characteristics of the system. The second objective is to develop an optimal management policy, through a quick search algorithm, to obtain the optimal values of the parameters r and R which minimise a suitable cost structure. This model is useful in different real-world operational management problems to minimise the organisation costs while keeping a high customer satisfaction level.

]]> 10.1504/IJAOM.2011.042139 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 175 - 187 Lotfi Tadj Chafik Abid School of Business Administration, Faculty of Management, Dalhousie University, Halifax, NS, B3H 3C3, Canada; Department of Finance, Information Systems and Management Science, Sobey School of Business, Saint Mary's University, Halifax, Nova Scotia, B3H 3C3, Canada. ' Department of Management, School of Business Administration, American University in Dubai, P.O. Box 28282, Dubai, United Arab Emirates Markov chain optimal policy semi-regenerative techniques single service queuing bulk service queuing general service time distributions operations management cost reduction customer satisfaction. 2011-08-28T23:20:50-05:00 3 2 175 187 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42140 Group technology and cellular manufacturing have renovated the method of manufacturing of mid-volume, mid-variety products. Many researchers have compared the performances of cellular manufacturing systems with those systems using process layouts. Such studies have brought out the merits and de-merits of both the systems and have helped in determining the suitable system for a given demand environment. They also give valuable information about the effect of factors like batch size, setup time, demand fluctuations, etc., on the performance of a manufacturing system and help in organising a selected system for better results. Previous studies suggest that the advantages of cellular manufacturing systems diminish in unstable demand. But the performance of adaptive cellular designs, which are suitable for dynamic demands, has not been tested. The best way to analyse the performance of manufacturing systems is by using simulation. This study compares, using simulation, the performance of an adaptive cellular layout with a process layout in dynamic demand. It is found that the adaptive cell design outperforms the process layout in average work-in-process inventory, average manufacturing lead-time and average waiting time of jobs. Performance comparison of process and adaptive cellular layouts using simulation
Jibi Job, Jerin Joseph, V. Madhusudanan Pillai
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 188 - 200
Group technology and cellular manufacturing have renovated the method of manufacturing of mid-volume, mid-variety products. Many researchers have compared the performances of cellular manufacturing systems with those systems using process layouts. Such studies have brought out the merits and de-merits of both the systems and have helped in determining the suitable system for a given demand environment. They also give valuable information about the effect of factors like batch size, setup time, demand fluctuations, etc., on the performance of a manufacturing system and help in organising a selected system for better results. Previous studies suggest that the advantages of cellular manufacturing systems diminish in unstable demand. But the performance of adaptive cellular designs, which are suitable for dynamic demands, has not been tested. The best way to analyse the performance of manufacturing systems is by using simulation. This study compares, using simulation, the performance of an adaptive cellular layout with a process layout in dynamic demand. It is found that the adaptive cell design outperforms the process layout in average work-in-process inventory, average manufacturing lead-time and average waiting time of jobs.

]]> 10.1504/IJAOM.2011.042140 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 188 - 200 Jibi Job Jerin Joseph V. Madhusudanan Pillai Department of Mechanical Engineering, National Institute of Technology Calicut, Calicut-673601, Kerala, India. ' Department of Mechanical Engineering, National Institute of Technology Calicut, Calicut-673601, Kerala, India. ' Department of Mechanical Engineering, National Institute of Technology Calicut, Calicut-673601, Kerala, India adaptive cell design process layout simulation performance comparison cellular manufacturing manufacturing cells work-in-process WIP inventory average lead times average waiting times. 2011-08-28T23:20:50-05:00 3 2 188 200 2011-08-28T23:20:50-05:00 http://www.inderscience.com/link.php?id=42141 This paper focuses on scheduling decision problems of a flexible manufacturing system (FMS) using simulation modelling and analysis. A typical FMS configuration is considered for the study. A discrete-event simulation model is developed for the purpose of experimentation. In this study, various scheduling rules are used for the decisions such as part launching, part routing and part sequencing. The performance of the system is evaluated using the measures such as mean flow time, mean tardiness, percentage of tardy parts, mean utilisation of machines and mean work-in-process. Based on the overall performance score, the combinations of scheduling rules for part launching, part routing and part sequencing decisions are ranked using the preference selection index method. Ranking of scheduling rule combinations in a flexible manufacturing system using preference selection index method
O.A. Joseph, R. Sridharan
International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 201 - 216
This paper focuses on scheduling decision problems of a flexible manufacturing system (FMS) using simulation modelling and analysis. A typical FMS configuration is considered for the study. A discrete-event simulation model is developed for the purpose of experimentation. In this study, various scheduling rules are used for the decisions such as part launching, part routing and part sequencing. The performance of the system is evaluated using the measures such as mean flow time, mean tardiness, percentage of tardy parts, mean utilisation of machines and mean work-in-process. Based on the overall performance score, the combinations of scheduling rules for part launching, part routing and part sequencing decisions are ranked using the preference selection index method.

]]> 10.1504/IJAOM.2011.042141 International Journal of Advanced Operations Management, Vol. 3, No. 2 (2011) pp. 201 - 216 O.A. Joseph R. Sridharan Department of Mechanical Engineering, KMCT College of Engineering, Kalanthode-673601, Manassery, Calicut, Kerala, India. ' Department of Mechanical Engineering, National Institute of Technology Calicut, NIT Campus P.O., Calicut 673-601, Kerala, India flexible manufacturing system FMS scheduling simulation scheduling rules preference selection index PSI modelling part launching part routing part sequencing. 2011-08-28T23:20:50-05:00 3 2 201 216 2011-08-28T23:20:50-05:00