Arash Ranjbaran Qadikolaei - Academia.edu (original) (raw)

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Papers by Arash Ranjbaran Qadikolaei

Research paper thumbnail of Lead time and ordering cost reductions in budget and storage space restricted probabilistic inventory models with imperfect items

RAIRO Oper. Res., 2015

Regarding today’s business environment restrictions, one of significant concern of inventory mana... more Regarding today’s business environment restrictions, one of significant concern of inventory manager is to determine optimal policies of inventory/production systems under some restrictions such as budget and storage space. Therefore here, a budget constraint on total inventory investment and a maximum permissible storage space constraint are added simultaneously to a stochastic continuous review mixed backorder and lost sales inventory system. This study also assumes that the received lot may contain some defective units with a beta-binomial random variable. Two lead time demand (LTD) distribution approach are proposed in this paper, one with normally distributed demand and another with distribution free demand. For each approach, a Lagrange multiplier method is applied in order to solve the discussed constrained inventory models and a solution procedure is developed to find optimal values. This study, also, shows that the respective budget and storage space constrained inventory m...

Research paper thumbnail of A stochastic multiobjective multiconstraint inventory model under inflationary condition and different inspection scenarios

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

This article presents inspection scenarios for the multiobjective multiconstraint mixed backorder... more This article presents inspection scenarios for the multiobjective multiconstraint mixed backorder and lost sales inventory model with imperfect items in which the order quantity, reorder point, ordering cost, lead time, and backorder rate are decision variables. The objectives are minimizing expected annual cost and variance of shortages. The number of imperfect items is assumed to be a beta-binomial random variable. There are two inspection scenarios: the imperfect items observed during inspection and screenings are either all reworked or all discarded. In order to fit some real environment, this study assumes the maximum permissible storage space and available budget are limited. Backorder rate is considered as a function of expected shortages at the end of cycle. Stochastic inflationary conditions with a probability density function are also considered in the presented model. This study assumes that the purchasing cost is paid when an order arrives at the beginning of the cycle, and the ordering cost is paid at the time of the order placing. The aggregate demand follows a normal distribution function. Finally, a solution procedure is proposed in order to solve the discussed multiobjective model. In addition, a numerical example is presented to illustrate the multiobjective model and its solution procedure for different inspection scenarios, and a sensitivity analysis is conducted with respect to the important system parameters.

Research paper thumbnail of A multi-item inventory system with expected shortage level-dependent backorder rate with working capital and space restrictions

international journal of industrial engineering computations, 2012

In this paper, a new multi-item inventory system is considered with random demand and random lead... more In this paper, a new multi-item inventory system is considered with random demand and random lead time including working capital and space constraints with three decision variables: order quantity, safety factor and backorder rate. The demand rate during lead time is stochastic with unknown distribution function and known mean and variance. Random constraints are transformed to crisp constraints with using the chance-constrained method. The Minimax distribution free procedure has been used to lead proposed model to the optimal solution. The shortage is allowed and the backlogging rate is dependent on the expected shortage quantity at the end of cycle. Two numerical examples are presented to illustrate the proposed solution method.

Research paper thumbnail of Lead Time Reduction in Budget and Storage Space Restricted Lot Size Reorder Point Inventory Models with Controllable Negative Exponential Backorder Rate

This study presents the mixed backorder and lost sales inventory models involving four variables;... more This study presents the mixed backorder and lost sales inventory models involving four variables; order quantity, lead time, safety factor (a discrete variable) and backorder rate. A controllable negative exponential backorder rate is considered in the proposed model. In the real market, as unsatisfied demands occur, the longer length of lead time is, the smaller proportion of backorder rate would be. Considering this reason, backorder rate is dependent on the length of lead time through the amount of shortages. The negative exponential lead time crashing cost is considered in this study. Today, the cost of land acquisition is high in most of the countries and one of the main concerns of inventory managers is to ensure that the maximum permissible storage space is enough when an order arrives. Hence, a random storage space constraint is considered, since, the inventory level is random when an order arrives. So, in this case, a chance-constrained programming technique is used to make it crisp. Moreover, another significant concern of inventory managers is how to control the maximum investment in the inventory. This study assumes the purchasing cost is paid at the time of order placing. Considering this assumption, a budget constraint is also added to the model in order to managing the maximum inventory investment. The lead time demand, first, follows a normal distribution and then, relaxes the distribution function assumption by only assuming the mean and variance of lead time demand are known and applies the minimax distribution free procedure to solve the problem. Furthermore, a numerical example is also given to illustrate the models and solution procedures.

Research paper thumbnail of Lead time and ordering cost reductions in budget and storage space restricted probabilistic inventory models with imperfect items

RAIRO Oper. Res., 2015

Regarding today’s business environment restrictions, one of significant concern of inventory mana... more Regarding today’s business environment restrictions, one of significant concern of inventory manager is to determine optimal policies of inventory/production systems under some restrictions such as budget and storage space. Therefore here, a budget constraint on total inventory investment and a maximum permissible storage space constraint are added simultaneously to a stochastic continuous review mixed backorder and lost sales inventory system. This study also assumes that the received lot may contain some defective units with a beta-binomial random variable. Two lead time demand (LTD) distribution approach are proposed in this paper, one with normally distributed demand and another with distribution free demand. For each approach, a Lagrange multiplier method is applied in order to solve the discussed constrained inventory models and a solution procedure is developed to find optimal values. This study, also, shows that the respective budget and storage space constrained inventory m...

Research paper thumbnail of A stochastic multiobjective multiconstraint inventory model under inflationary condition and different inspection scenarios

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

This article presents inspection scenarios for the multiobjective multiconstraint mixed backorder... more This article presents inspection scenarios for the multiobjective multiconstraint mixed backorder and lost sales inventory model with imperfect items in which the order quantity, reorder point, ordering cost, lead time, and backorder rate are decision variables. The objectives are minimizing expected annual cost and variance of shortages. The number of imperfect items is assumed to be a beta-binomial random variable. There are two inspection scenarios: the imperfect items observed during inspection and screenings are either all reworked or all discarded. In order to fit some real environment, this study assumes the maximum permissible storage space and available budget are limited. Backorder rate is considered as a function of expected shortages at the end of cycle. Stochastic inflationary conditions with a probability density function are also considered in the presented model. This study assumes that the purchasing cost is paid when an order arrives at the beginning of the cycle, and the ordering cost is paid at the time of the order placing. The aggregate demand follows a normal distribution function. Finally, a solution procedure is proposed in order to solve the discussed multiobjective model. In addition, a numerical example is presented to illustrate the multiobjective model and its solution procedure for different inspection scenarios, and a sensitivity analysis is conducted with respect to the important system parameters.

Research paper thumbnail of A multi-item inventory system with expected shortage level-dependent backorder rate with working capital and space restrictions

international journal of industrial engineering computations, 2012

In this paper, a new multi-item inventory system is considered with random demand and random lead... more In this paper, a new multi-item inventory system is considered with random demand and random lead time including working capital and space constraints with three decision variables: order quantity, safety factor and backorder rate. The demand rate during lead time is stochastic with unknown distribution function and known mean and variance. Random constraints are transformed to crisp constraints with using the chance-constrained method. The Minimax distribution free procedure has been used to lead proposed model to the optimal solution. The shortage is allowed and the backlogging rate is dependent on the expected shortage quantity at the end of cycle. Two numerical examples are presented to illustrate the proposed solution method.

Research paper thumbnail of Lead Time Reduction in Budget and Storage Space Restricted Lot Size Reorder Point Inventory Models with Controllable Negative Exponential Backorder Rate

This study presents the mixed backorder and lost sales inventory models involving four variables;... more This study presents the mixed backorder and lost sales inventory models involving four variables; order quantity, lead time, safety factor (a discrete variable) and backorder rate. A controllable negative exponential backorder rate is considered in the proposed model. In the real market, as unsatisfied demands occur, the longer length of lead time is, the smaller proportion of backorder rate would be. Considering this reason, backorder rate is dependent on the length of lead time through the amount of shortages. The negative exponential lead time crashing cost is considered in this study. Today, the cost of land acquisition is high in most of the countries and one of the main concerns of inventory managers is to ensure that the maximum permissible storage space is enough when an order arrives. Hence, a random storage space constraint is considered, since, the inventory level is random when an order arrives. So, in this case, a chance-constrained programming technique is used to make it crisp. Moreover, another significant concern of inventory managers is how to control the maximum investment in the inventory. This study assumes the purchasing cost is paid at the time of order placing. Considering this assumption, a budget constraint is also added to the model in order to managing the maximum inventory investment. The lead time demand, first, follows a normal distribution and then, relaxes the distribution function assumption by only assuming the mean and variance of lead time demand are known and applies the minimax distribution free procedure to solve the problem. Furthermore, a numerical example is also given to illustrate the models and solution procedures.