2020-01-28T20:06:01Z
http://www.jise.ir/?_action=export&rf=summon&issue=633
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
Door Allocations to Origins and Destinations at Less-than-Truckload Trucking Terminals
Vincent F.
Yu
Dushyant
Sharma
Katta G.
Murty
For an LTL (Less-than Truckload) carrier, the allocation of doors at a consolidation facility to outbound trailers assigned to various destinations, and to inbound trailers in the continuous stream arriving from various origins, has a significant impact on its operations, and on the nightly man-hours needed for consolidation. In the past literature door allocations to destinations of outbound trailers are determined using deterministic mathematical models based on average volumes of shipments between origin-destination pairs. The online nature of allocation of doors to inbound trailers is either ignored or simple rules like FCFS (First Come First Served) are assumed that do not take advantage of the data on the trailer's actual contents readily available at the time of its arrival. In reality the actual shipment volume between any origin-destination pair varies significantly from day to day. Due to this wide variation destination door allocations that are optimal for the average volume tend to be far from optimum for most nights. Also, very simple on-line policies for door allocation to each inbound truck at the time of its arrival based on its actual contents can significantly reduce the man-hours needed to consolidate its contents. In this paper we develop a new model that uses such an on-line policy for door allocations to inbound trailers, and determines doors to allocate to destinations to minimize the expected man-hours for consolidating freight nightly taking the random variation in freight volumes into account. Computational results on data from an actual facility indicate that the man-hour requirement can be reduced by over 20% compared to current practice.
cross-docking
Less-than-truckload freight terminal
Man-hours for consolidation
2008
04
01
1
15
http://www.jise.ir/article_3948_24fced7e8935833da864ec4e16587021.pdf
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
Determining Optimal Number of Suppliers in a Multiple Sourcing Model under Stochastic Lead Times
Mohammad Reza
Akbari Jokar
Mohsen
Sheikh Sajadieh
Employing more than one supplier and splitting orders between them is a strategy employed in supply chains to lessen the lead-time risk in unstable environments. In this paper we present a multiple-sourcing inventory system with stochastic lead-times and constant demand controlled by a continuous review, reorder point-order quantity inventory policy. We consider the situation in which the order quantity is equally split between a number of identical suppliers. The aims of this research are to determine the optimal number of suppliers and analyze the percentage savings obtained in a multiple-sourcing system compared to sole-sourcing. The objective function is to minimize the expected total cost per unit time by obtaining the number of suppliers, the reorder point and order quantity as decision variables. Extensive numerical examples are used to examine the effects of different parameters on the percentage savings and the optimal number of suppliers.
Multiple-sourcing
Lead-time risk pooling
Stochastic lead times
2008
04
01
16
27
http://www.jise.ir/article_3949_20eaf78927377cf8c0b30a41dca8f86d.pdf
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
Modeling of a Probabilistic Re-Entrant Line Bounded by Limited Operation Utilization Time
Suresh
Kumar
This paper presents an analytical model based on mean value analysis (MVA) technique for a probabilistic re-entrant line. The objective is to develop a solution method to determine the total cycle time of a Reflow Screening (RS) operation in a semiconductor assembly plant. The uniqueness of this operation is that it has to be borrowed from another department in order to perform the production screening task. Since the operation is being shared, there is a time limit to utilize it in a day. Screening of lots that cannot be completed within the given time has to be continued in the following days. The contributions of this paper is the development of a lot clustering method and factoring the limited time sharing condition and thus develop an analytical model. Comparison results were made using available real historical data. The proposed model provided operation managers with the total cycle time computation method and determining the appropriate cluster size to be loaded into the operation.
Probabilistic re-entrant line
Mean value analysis
Lot clustering
Total cycle time
2008
04
01
28
40
http://www.jise.ir/article_3950_9efda8d8263280d19fcc6482b58c1351.pdf
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
Deriving the Exact Cost Function for a Two-Level Inventory System with Information Sharing
R.
haji
S.M.
Sajadifar
In this paper we consider a two-level inventory system with one warehouse and one retailer with information exchange. Transportation times are constant and retailer faces independent Poisson demand. The retailer applies continuous review (R,Q)-policy. The supplier starts with m initial batches (of size Q), and places an order to an outside source immediately after the retailerâ€™s inventory position reaches R+s. In this system the lead time of the retailer is determined not only by the constant transportation time but also by the random delay incurred due to the availability of stock at the supplier. A recent paper has obtained the approximate value of the expected cost for this system by using the expected value of the retailerâ€™s lead time and hence has pointed out that the optimal supplier policy is an open question. In this paper we tackle this open question and obtain the exact value of the expected system cost by using the idea of the one-for-one ordering policy and implicitly incorporating the distribution function of the random delay.
Multi-echelon inventory
information sharing
Continuous review
Poisson demand
2008
04
01
41
50
http://www.jise.ir/article_3951_1afa6b1b3d1014c48f0bc482cbb10110.pdf
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
An EFQM Based Model to Assess an Enterprise Readiness for ERP Implementation
Rasoul
Shafaei
Nooraddin
Dabiri
In today's competitive market, Enterprise Resource Planning (ERP) system is widely being used by industries. However, the results of the research efforts carried out in this field reveal that the rate of successful implementations for ERP projects is low and in most cases the planned goals are not achieved. Therefore it is necessary to assess maturity of an enterprise in terms of factors affecting a successful implementation of an ERP system. This paper proposes an EFQM based model to assess the readiness of an enterprise for effective and successful ERP implementation. First, the main factors affecting the implementation of an ERP system, called Critical Success Factors (CSF) are identified. Then relations between the factors defined in EFQM model and ERP CSFs are investigated by means of questionnaires by experts working in this field. The results identify those EFQM factors which are related to ERP CSFs. In addition, those ERP specific factors which are not considered in the EFQM model are identified. Consequently a model based on EFQM including ERP specific CSFs is developed. The proposed model is applied to assess the readiness of a company intending to implement an ERP system. Finally the results of the assessment are discussed and concluding remarks are presented.
Enterprise resource planning
Readiness assessment
Critical success factors
EFQM
2008
04
01
51
74
http://www.jise.ir/article_3952_0f223eb3c22a4ac67f5bc85056c315b6.pdf
Journal of Industrial and Systems Engineering
jise
1735-8272
1735-8272
2008
2
1
Some Modifications to Calculate Regression Coefficients in Multiple Linear Regression
S.M.
Sajadifar
M.
Allameh
In a multiple linear regression model, there are instances where one has to update the regression parameters. In such models as new data become available, by adding one row to the design matrix, the least-squares estimates for the parameters must be updated to reflect the impact of the new data. We will modify two existing methods of calculating regression coefficients in multiple linear regression to make the computations more efficient. By resorting to an initial solution, we first employ the Sherman-Morrison formula to update the inverse of the transpose of the design matrix multiplied by the design matrix. We then modify the calculation of the product of the transpose of design matrix and the design matrix by the Cholesky decomposition method to solve the system. Finally, we compare these two modifications by several appropriate examples.
Regression
Inverse matrix
Cholesky decomposition
Sherman-Morrison -
Woodbury formula
2008
04
01
75
86
http://www.jise.ir/article_3953_4d220fa82390cf449a34d3bd61f83762.pdf