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When making sourcing decisions, both cost optimization and customer demand fulfillment are equally important for firm competitiveness. The purpose of this paper is to develop a stochastic search technique, hybrid genetic algorithm (HGA), for cost-optimized decision making in wholesaler inventory management in a supply chain network of wholesalers, retailers and suppliers.

This study develops a HGA by using a mixture of greedy-based and randomly generated solutions in the initial population and a local search method (hill climbing) applied to individuals selected for performing crossover before crossover is implemented and to the best individual in the population at the end of HGA as well as gene slice and integration.

The application of the proposed HGA is illustrated by considering multiple scenarios and comparing with the other commonly adopted methods of standard genetic algorithm, simulated annealing and tabu search. The simulation results demonstrate the capability of the proposed approach in producing more effective solutions.

The pragmatic importance of this method is for the inventory management of wholesaler operations and this can be scalable to address real contexts with multiple wholesalers and multiple suppliers with variable lead times.

The proposed stochastic-based search techniques have the capability in producing good-quality optimal or suboptimal solutions for large-scale problems within a reasonable time using ordinary computing resources available in firms.

This paper examines the sensitivity of the Economic Order Quantity (EOQ) inventory model to lot size errors when the purchase cost per unit, C, and the replenishment cost per order, A, are both dependent on the amount ordered, Q. A formula for the percentage increase in average annual variable costs due to using a Q‐value different from Q is derived, and is shown to be the same as that for the simple EOQ and backorders model.

Inventory service levels are a concern of every inventory system. Poor service levels may result in loss of customers and sales, whereas excessive service levels result in loss of money due to large inventories. Although inventory service levels have been discussed widely in the professional literature, the emphasis has been on service levels during replenishment lead times. Overall service levels, which are much more relevant to customers, have received little attention, and the results presented are often mistaken. This article reviews measures of inventory service levels both for single and multiple items, relates single item measures during lead times to their overall counterparts, and shows that overall measures are not only more relevant to customers, but also require lower safety stock from the provider of the goods.

The main streams of the supply chain are defined as material, information and financial flow. There have been many studies and practical cases regarding the flow of material and information including information sharing. However, financial flow related studies have not been widely examined relatively, compared with their importance.

The information sharing is recognized as the method that can reduce the Bullwhip effect in supply chain management. The author intends to analyze the impact of financial information sharing on the results of the supply chain.

In the point of supply chain risk management view, the author examined the impact of financial flow among the various factors that can impede the stability of the supply chain.

In this study, the author embodied the simulation regarding the impact of financial information flow on supply chain performance and stability based on the system dynamics methodology and analyzed the performance.

Assuming the supply chain, composed of supplying company, manufacturing company and sales company , the author embodied the simulation model and assumed that working capital and cash information sharing were achieved. The author embodied the model to affect the settlement conditions according to the results of financial information sharing.

Performance improvement for requirements planning systems is an issue which receives wide interest. Many programming approaches have been proposed to improve material requirements planning procedures. However, most of them appear to be too complex for large manufacturing problems. Alternatively it might be promising to explore the integration of materials requirements planning and capacity requirements planning. Several simple heuristics for integrated requirements planning systems are suggested. Several heuristics are offered to balance the load in the systems and several procedures presented to adjust the planned requirements so that the system will execute more smoothly. An industrial example supports the adequacy of the general concepts provided in this research. Results are presented which demonstrate the adequacy of these heuristics, and illustrate the ease of implementing the procedures into any MRP system.

Purpose – The purpose of this study is to explore the concept of the economic lot sizing and the time cycle period of reordering. The stochastic demand is quite common in the real environment of a cement retailer. The study compares three methods to obtain the optimal solution of a lot-sizing ordering from the real case of the previous study where the dataset is collected from the area of some retailers at Banda Aceh Province of Indonesia.

Design/Methodology/Approach – The problem model appears when the retailer with shortage has to fulfill the lot size in the optimal condition to the stochastic demand while at the same time has the backlog condition. Moreover, when the backorder needs the time horizon for replenishment where this condition influences the holding cost at the store, many retailers try to solve this problem to minimize the holding cost, but on the other side, it should fulfill the customer demand. Three methods are explored to identify that condition: a Wagner–Whitin algorithm, the Silver–Meal heuristic, and the holding and ordering costs. The three methods are applied to the lot sizing when there is a backlog.

Findings – The results of this study show that the Wagner–Whitin algorithm outperforms the other two methods. It shows that the performance increases around 27% when compared to the two other methods in this study.

Research Limitations/Implications – All models are almost approximate and useful to determine the cycle period on stochastic demand.

Practical Implications – The calculation of the dataset with the three methods would give the simple example to the retailer when he faces the uncertainty demand models. The prediction of the calculation is done accurately than the constant calculation, which is more economic.

Social Implications – The calculation will contribute to much better predictions in many cases of uncertainty.

Originality/Value – This is a initial comparative model among other methods to achieve the optimal stock and order for a retailer

This paper proposes a new inventory model with inspection policy because in practice the received orders may contain non- conforming (NC) items. So, a buyer who receive an order from a supplier should use an inspection policy.

The inspection policy is assumed to be zero-defect single sampling. Under this policy a lot is accepted only if no defect has been identified in the inspected sample. The fraction of NC is assumed to be a random variable following a Binomial distribution and the number of NC items detected by inspection assumed to be a random variable, which follows a hypergeometric distribution. Order quantity and sample size are the two decision variables. A solution procedure is presented for the proposed model. The proposed procedure presents the optimal solution.

Numerical examples presented to illustrate the procedure outlined for the proposed model and its applicability. The results of numerical examples and comparing them with traditional EOQ model reveal that by the proposed model, the buyer could reduce total cost that shows the efficiency and validity of the proposed model.

The novelty of this paper is the new proposed model that considers inspection policy in inventory management. The proposed model determines sample size as well as order quantity to consider both subject of inventory management and quality control, simultaneously.

The present paper aims to draw an attention towards the inclusion of forecast related costs. Its main purpose is to initiate a new line of research/practice including the forecasting expenditure.

After a relevant review of supply chain/procurement/production planning related literature, it has been observed that the existing work lacks an explicit inclusion of the cost concerned with forecast. The increased cost of forecasting is expected to enhance the forecasting accuracy. At a higher level, product family is considered for the analysis. However, a basic unit of analysis is always a single item production/procurement situation. Therefore, this situation has been discussed analytically with the use of the fundamental equations and an explicit inclusion of forecasting cost for the first time in the relevant literature. Numerous practical applications have been discussed at strategic and operational level. A framework is also presented for future research in this area.

A specific contribution of the present paper is an approach towards a unique index for relative forecasting expenditure. The suggested index will be useful for comparison purpose. Also, it can be used as a benchmark that can be improved in future.

The case is explained when cycle time is invariant after discussing the other potential applications. Usefulness of the proposed methodology and the index is discussed for the business organizations operating independently or in the supply chains.

On the basis of the forecast, a production or procurement plan is generated in many of the industrial or business situations. In the context of supply chain/production/inventory management, focus is more on demand forecasting techniques or generation of the forecasts in the existing literature. However, the increased costs concerning forecasts are expected to provide more accurate prediction. Therefore, the originality lies in an inclusion of forecast related costs.

Current studies indicate that buyers can improve lead‐time performance and reduce total inventory‐system costs by splitting orders between two suppliers. These studies, however, treat transportation only implicitly as an element of the cost of placing an order. This is an important limitation, because shipping costs increase disproportionately as the size of shipment decreases and typically comprise a sizeable portion of total logistics cost. Investigates the role of transportation in the decision to procure from either one or two suppliers. A state‐of‐the art model was first modified to treat transportation costs explicitly and then used to conduct 54 experiments to measure the gains or losses in total logistics costs under a variety of representative conditions.

The purpose of this paper is to discuss the ways in which organisations embedding key performance indicators (KPIs) as part of their organisational activities. Specifically this paper shows the role of cultural change programme in enabling the implementation of KPIs in the context of this study.

The present study was conducted using ethnographic approach. Consistent with tradition in doing ethnographic studies, observation was the main method employed in this study. Additionally, this study employed interview and document review methods.

This study concludes that the operation of KPIs in this organisation were made to work through a programme of cultural change. This finding suggests that accounting measurements such as KPIs can be embedded as part of organisational activities through cultural intervention.

This study provides empirical evidence of the actions people do in making performance measurement works in organisations.

This study adds to the limited number of literatures that link culture and performance measurement.