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Supply chain flexibility has long been recognized as an important strategic and operational characteristic of manufacturing systems and organizations. In general, supply chain flexibility allows firms to compete more effectively in a world of short product life cycles, rapid product development, and substantial demand and/or price uncertainty. Outsourcing option is one of the most important strategic decisions which can improveorganization’s supply chain flexibility. A real options approach is a tool, which can estimate the value of flexibility and is used to determine the optimum strategy to manage this flexibility. The main objective of this paper is to develop a simulation model to evaluate the option value of outsourcing and examine its effect on supply chain flexibility using real options approach. The proposed model demonstrates the application of real options approach to value outsourcing option in order to enhance the organization’s supply chain flexibility through four variables: price, quality, delivery, and switching ability. Several examples through different scenarios are presented, carried out and simulated using Monte Carlo simulation. The proposed approach givesdecision makers a way to choose the appropriate outsourcing strategy based on an integrated view of market dynamics.

Most papers model Joint Replenishment Problem (JRP) as a (kT,S) where kT is a multiple value for a common review period T,and S is a predefined order up to level. In general the (T,S) policy is characterized by a long out of control period which requires a large amount of safety stock compared to the (R,Q) policy. In this paper a probabilistic model is built where an item, call it item(i), with the shortest order time between interval (T)is modeled under (R,Q) policy and its inventory is continuously reviewed, while the rest of items (j) are periodically reviewed at a definite time corresponding to item, {"references":["Atkins, D., Iyogun, P., 1988. Periodic versus can order policies for\ncoordinated multi-item inventory system. Management Science 34 (6),\n791-796.","Axsater, S., 2004.Inetory Control, Kluwer Academic Publisher Group.","Eryan, A., Kropp, D.H., 2007. Effective and simple EOQ-like solutions\nfor stochastic demand periodic review systems. Eur. J. Oper. Res. 180,\n1135-1143.","Eryan, A., Kropp, D.H., 1998. Periodic review and joint replenishment\nin stochastic demand environment.IIE Transactions 30, 1025-1033.","Fung, R., MA, X., 2001.Anew method for joint replenishment problems.\nJournal of Operational Research Society52, 358-362.","Forsberg, R., 1995. Optimization of order-up-to S policies for two-level\ninventory systems with compound Poisson demand. European Journal of\nOperational Research 81.","Goyal, S.K., 1973. Determination of economic packaging frequency for\nitems jointly replenished. Management Science 20 (2), 232.","Goyal, S.K., 1974. Determination of optimum packaging frequency of\nitems jointly replenished. Management Science 21 (4), 436-443.","Hariga, M., 1994. Two new heuristic procedures for the joint\nreplenishment problem, Journal of the Operational Research Society 45\n463-471.\n[10] Johansen, S.G., Melchior P., 2003. Can-order policy for the periodicreview\njoint replenishment problem, Journal of the Operational Research\nSociety 54 283-290.\n[11] Larsen,C., 2008.The Q(s,S) control policy for the joint replenishment\nproblem extended to the case of correlation among item-demand.\nJournal of Production Economics,doi:10.1016/j.ijpe.2008.08.025\n[12] Olsen, A.L., 2005. An evolutionary algorithm to solve the joint\nreplenishment problem using direct grouping. Computers and Industrial\nEngineering 48 (2), 223-235.\n[13] Pantumsinchai, P., 1992. A comparison of three joint ordering inventory\npolicies. Decision Science 23, 111-127.\n[14] Porras E. and Dekker R. 2005. An efficient optimal solution method for\nthe joint replenishment problem with minimum order quantities.\nEuropean Journal of Operational Research (forthcoming)\n[15] Silver, E.A., 1976. A simple method of determining order quantities in\njoint replenishments under deterministic demand. Management Science\n22 (12), 1351-1361.\n[16] Van Eijs, M.J.G., 1993. A note on the joint replenishment problem under\nconstant demand. Journal of Operational Research Society 44 (2), 185-\n191.\n[17] Viswanathan, S., 1996. A new optimal algorithm for the joint\nreplenishment problem. Journal of Operational Research Society 47 (7),\n936-944.\n[18] Viswanathan, S., 2002. On optimal algorithms for the joint\nreplenishment problem. Journal of Operational Research Society 53\n(11), 1286-1290.\n[19] Wildeman, R.E, Frenk, J.B.G., Dekker, R., 1997. An efficient optimal\nsolution for the joint replenishment problem. European Journal of\nOperational Research 99, 433-444.\n[20] Zheng, Y.S., Federgruen, A., 1991. Finding optimal sً; S قpolicies is\nabout as simple as evaluating a single policy. Operations Research 39\n(4), 654-665.\n[21] Zipkin, P., 2000. Foundations of Inventory Management. McGraw-Hill."]}

An inventory system with one warehouse and one retailer is proposed, planned shortage inventory amounts are allowed at both the retailer and the warehouse. During the ordering process, a major order cost for the lot is incurred at each location and a minor order cost is added for each item in the lot. Demand occurs only at the retailer with a constant deterministic rate. Two policies are considered for this problem; first, the centralised non-cooperative policy where a centralised decision making process is done on warehouse and retailer together to optimise their costs; second, the centralised cooperative policy wherein addition to the centralised decision process, the items at the retailer and the warehouse are replenished jointly to gain the advantage of reducing the major order cost. In the first policy, the objectives here are to evaluate the optimum order interval for each item (i), while in the second policy the objectives are to determine the common order interval, the associated multiple integers and that determines the time of order for each item, and the optimum inventory planned shortage amounts, for each item at each location, which minimise the total inventory cost for the echelon system.

Primary and secondary cultures of VX-2 carcinoma produced high levels of collagenase activity in both active and latent forms in serum-free media. These cultures appeared morphologically heterogeneous in phase-contrast microscopy and revealed the presence of mainly three distinct forms; epithelial-like cells (E cells), fibroblast-like cells (F cells), and large rounded-flat cells which may represent a subclass of the F cells. Cell separation techniques such as brief dispase treatment, Percoll gradient centrifugation, thimerosal treatment, and rabbit serum were used to obtain predominantly one form or the other. The E cells never formed a monolayer but rather grew as limited size clusters of intimately associated cells with large nuclei and often appeared multinucleated. These cells were difficult to maintain in culture or serially passed more than a few times. The F cells, rare in early cultures but having the highest growth potential, appeared in various morphological forms ranging from spindle- to stellate-shaped cells. The cells in their third passage were capable of producing palpable tumors, similar in light and electron microscopic studies to the original tumor from which they were derived, when injected intramuscularly into recipient rabbits and produced specific collagenase activity in active and latent forms in serum-free media. Ultrastructural studies suggested that the E cells were of epithelial origin whereas the F cells were similar to stromal fibroblasts. Cytogenetic studies demonstrated that almost all of the E cells showed both numerical and structural chromosomal changes in a modal number of 54 chromosomes. On the other hand, the major cell population of the F cells resembled normal rabbit fibroblasts; both contained a normal diploid (2 n = 44). However, few cells (4–6%) in the F-cell population were hyperdiploid with a modal chromosome number of 54. These cells may represent inadvertent contaminating E cells and account for the apparent limited turmorigenicity observed in early F-cell cultures. The data suggested that the E cells were of tumor origin whereas the majority of the F-cell population appeared to be of host origin. Furthermore, it is suggested that the E cells stimulate tumor-associated stromal cells to produce elevated levels of collagenolytic activity and contribute to collagen degradation during tumor invasion.

Fibroblast-like cells (F-cells) and epithelial-like (E-cells) derived from cultures of rabbit VX-2 carcinoma released collagenase in both active and latent forms in serum-free medium at a level higher than that of normal rabbit fibroblast cultures. The enhanced capacity of the F-cells to release the enzyme, however, continued only for a few passages and then decreased significantly to a low level similar to that of the normal fibroblasts. The enzyme-release by the E-cells continued for a few more passages at a relatively moderate level, higher than that of normal fibroblasts. The release of collagenase in cultures of F-cells was enhanced by the presence of E-cells in mixed cultures as well as by medium conditioned by the E-cells type. Addition of cytochalasin B at 2 micrograms/ml did not significantly effect the enzyme activity released in the cultures. Serum from tumor-bearing rabbits appeared to stimulate the release of enzyme activity in cultures of either cell type.