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(1994). Optimal Design of Experiments. Journal of the Operational Research Society: Vol. 45, No. 8, pp. 961-962.

A heuristic decision rule is derived for the replenishment of items with a linearly increasing demand rate over a finite planning horizon during which shortages are allowed. When compared with the exact decision rule, the heuristic is found to incur negligible cost penalty for the numerical example which is given to illustrate the use of the heuristic.

Maximum likelihood estimates for the parameters involved in a stationary M/M/2 queueing process with heterogeneous servers are obtained to make inferences about arrival and service rates. The queue is considered to be in a state of equilibrium. One further extension is discussed.

A single-item order-level lot-size-type inventory model is developed for items with a deterministic time-dependent demand. Shortages are allowed during the fixed finite planning horizon whose initial and final inventory levels are zero. A general inventory model is developed first and then an exact solution for the particular case of the linearly increasing demand rate is derived. An operating schedule for calculating the optimal solution is suggested. A numerical example is also given.

A lot-size model is developed in which the demand is changing linearly with time. The model is continuous in units and discrete in time. The planning horizon is finite and known with equal replenishment periods. The problem is to find the optional number of replenishments which are instantaneous. An example followed by Sensitivity analysis is given to illustrate the derived model.

A probabilistic scheduling-period inventory model continuous in units and discrete in time is developed for deteriorating items where deterioration is assumed to be a constant fraction of the on-hand inventory. The model is developed under the conditions of instantaneous delivery and no shortages. An example followed by sensitivity analysis is given to illustrate the derived results.

The problem of returning or of selling the inventory excess to optimal stock level is considered for deteriorating items. Two inventory models, viz. the infinite and the finite horizon models, are developed, in which the deterioration is assumed to be a constant fraction of the on hand inventory. Both the models are developed under the assumptions of instantaneous delivery and no shortages. When there is no deterioration, the developed models are related to the corresponding inventory models for non-deteriorating items. Examples are given to illustrate the derived results.

A probabilistic inventory model for continuously deteriorating items is developed, in which the lead time is assumed to be of one scheduling period, shortages are not allowed, time is treated as discrete variable, and deterioration is assumed to be a constant fraction of the on hand inventory. The developed model is related to the EOQ model for deteriorating items. An example is given to illustrate the derived results.

An EOQ model is reconsidered here in which the demand rate is changing linearly with time and the deterioration is assumed to be a constant fraction of the onhand inventory. The planning horizon is finite and known and the replenishment periods are assumed to be constant. The problem is to find the optimal number of replenishments, which are instantaneous. When there is no deterioration, the model developed is related to the corresponding model for nondeteriorating items. An example followed by sensitivity analysis is given to illustrate the derived results.

(1987). Applied Probability and Queues. Journal of the Operational Research Society: Vol. 38, No. 11, pp. 1095-1096.

(1985). On “Economic Order Quantity under Conditions of Permissible Delay in Payments” by Goyal. Journal of the Operational Research Society: Vol. 36, No. 11, pp. 1069-1069.

An Order-Level inventory model continuous in units and discrete in time is developed for deteriorating items. The model is developed under deterministic demand and instantaneous delivery. Deterioration is assumed to be a constant fraction of the onhand inventory. An example is given to illustrate the model.