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The purpose of this paper is to develop a multi-item economic production quantity (EPQ) strategy under grey environment and space constraint. Since the “demand” cannot be predicted with certainty, it is assumed that data behave under grey environment and compare the proposed inventory model with other studies using crisp or fuzzy environments.

This paper is to optimise the cycle time and total cost of the multi-item EPQ inventory model. For this purpose, the Lagrangian coefficient is used to solve the constrained optimisation problem. The grey relational analysis approach and grey data are applied in developing the EPQ inventory model.

The results are compared with the analysis using crisp and fuzzy data. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The results of the study demonstrate that crisp data outperform the other two data in all scales problems in terms of cycle time and cost; grey data perform better in all scales problems than fuzzy data.

The contribution of this research is the use of grey data in developing the EPQ inventory model with space constraint.

Supply chain management (SCM) focuses smart logistics and quality service. Diverse elements such as design, procurement, production and sale policies are the keys to SCM efficiency. Due to worsening environmental pollution in recent years, many businesses, government agencies and consumers have become more aware of greenhouse gases (GHG) emissions. In response, the government has established new environmental regulations to control various GHG, such as CO₂ and sulfur dioxide. Therefore, to reduce pollution and its adverse effects, the authors have promoted environmental concerns by developing environmental friendly policies. The purpose of this paper is to develop a multi-objective decision making model that integrates both forward and reverse logistics to determine how best to incorporate recycling and reduce manufacturing costs.

In this study, the authors developed a multi-objective decision-making model that integrates both forward and reverse logistics to determine how best to incorporate recycling and reduce manufacturing costs. They used the normalized normal constraint method as proposed by Messac et al. (2003) to generate a series of uniform lines on a Pareto Frontier chart.

Based on the results of this study, the authors can determine the trade-off between costs and emissions and design the most environmental-friendly and economical strategy for production.

This study is limited to a case study on paper manufacturing.

The authors considered the full truckload discount policy in which buyers can reduce their purchase costs by increasing the number of full truckload product orders; this will reduce transportation costs and also minimize overall carbon emissions.

This study encourages industries to focus on environmental friend policies and social responsibilities.

The authors investigated the impacts of the paper making industry on economy and environment. An increase in demand will negatively impact the environment by causing CO₂ emissions to increase from higher production and the felling of more trees to provide raw materials for manufacturers (paper mills).

External factors such as improper handling, extreme weather and insect attacks affect product quality. It is most obvious in fruit products which have a high deterioration rate. Moreover, decaying fruits will increase the deteriorating of other good ones. The purpose of this study is to derive the optimal pricing and replenishment decisions for agricultural products considering the effect of external factors that induce deterioration.

In this paper, the study investigates ways to reduce the product deterioration rate by separating the near defective items from the other good products and accelerating the quick sales of the near defective items at a discounted price. The objective is to maximize the total profit by optimizing the selling price and the replenishment cycles. Two scenarios are investigated. In the first scenario, the retailer offers a selling price discount for near defective products to stimulate customer demand. In the second scenario, the retailer does not offer such discounts.

An algorithm to solve the model is derived. Further, numerical examples are developed to compare the total profit for the two scenarios. Theoretical derivations and graphical results show the concavity of the profit function. Finally, the sensitivity analysis shows that the total profit of the discount model is higher.

This study contributes to a new pricing and inventory decision model. The research provides insights to retailers on making optimal pricing and replenishment decisions for non-instantaneous deterioration items, as well as reducing the external factors that influence higher deterioration rate through separating good products from the near defective ones which are sold at a discount to induce the sale.

Nowadays, uncertainty in market demand poses considerable risk to the retailers that supply the market. On the other hand, the risk-averse behaviors of retailers toward risk may have evolved over time. Considering a supply chain including a manufacturer and a population of retailers, the authors intend to investigate how the population of retailers tends to evolve toward risk-averse behavior. Moreover, this study aims to evaluate the effects of wholesale-retail price of manufacturer on evolutionary stable strategy (ESS) of the retailers.

Due to market uncertainty, a supply chain with a population of risk-averse and risk-neutral retailers was investigated. The wholesale pricing strategy is determined by a manufacturer acting as a leader, while retailers who make order quantity decisions act as followers. An integrated Cournot duopoly equilibrium and evolutionary game theory (EGT) approach has been used to model this situation.

A numerical real-world case study using Iran Khodro Company is analyzed by applying the proposed EGT approach. The study provides managerial insights to the manufacturer as well as retailers in developing their strategies. Results showed that risk behavior of retailers significantly affects optimal wholesale/retail price, profits and ESS. In the long term, the retailers tend to have a risk-neutral behavior to gain more profit. In the short term, if a retailer choses risk-averse strategy, in the long term, it will change its strategy to obtain more profit and remain in the competitive market.

The contributions in this research are fourfold. First, ESS concept to investigate the risk-averse or risk-neutral attitudes of the retailers was used. Second, the uncertain risk behavior of the competing retailers was considered. Third, the effect of varying wholesale pricing was investigated. Fourth, the equilibrium wholesale and retail prices have been obtained by considering uncertainty demand and risk.

This paper aims to simultaneously consider an inventory model with price and advertisement dependent demand, non-instantaneous deterioration rate with preservation technology investment, partially backlogged shortages and trade credit.

This model considered a non-instantaneous deterioration, which starts after a certain storage period with a constant rate. The proposed model focused on two things. The first one is to reduce the deterioration rate by preservation technology investment, and the second one is using an appropriate trade credit period to maximize the total profit. The classical optimization technique is used to solve the problem.

The authors found that trade credit, advertising cost, preservation technology affect the total cost and selling price is one of the most important decision variables affecting the model.

This study provides a reference for a manufacturer and a retailer on making inventory decisions under different pricing, advertisement expense, preservation technology investment and credit strategies. Four cases are presented to illustrate the inventory model. Sensitivity analyses are performed to gain managerial insights for decision-making.

The study simultaneously considers a non-instantaneous deterioration inventory model, trade-credit, and preservation technology and advertisement policy. From our literature search, no researcher has undergone this type of study.

Study in supply chain performance research on the shipbuilding industry is lacking. The purpose of this research is to study and provide guidelines to improve the performance of traditional shipbuilding supply chains in Indonesia.

The paper develops an empirical study gathered from a traditional shipbuilding industry, its suppliers, and customers. This study consists of three sections: the traditional shipbuilding industry, the suppliers, and the individual supplier scores. The internal and external performances in this study are measured using Supply Chain Operations Reference (SCOR) metrics. The SCOR model identifies five performance measurement attributes, including reliability, flexibility, responsiveness, cost and assets. Instead of using “responsiveness,” this study applies the schedule performance index, and supplements “cost” with the cost performance index in order to accurately reflect the traditional shipbuilding supply chains processes.

By analyzing SCOR metrics in the traditional shipbuilding industry, it has been found that the ideal shipbuilding supply chain metrics are order fulfillment, flexibility, asset turnover and total supply chain costs. The lowest performance metric value in the traditional shipbuilding industry is the cost of goods. Some improvements are proposed to lower the high cost of ship building. An integrated economic ordering system in collaboration with all the suppliers is one of the most effective ways to reduce the cost of the traditional shipbuilding supply chains. The implementation of SCOR metrics enables management to identify the critical issues to improve.

The study applies SCOR metrics to improve the traditional shipbuilding supply chains performance. The study is limited because the data collected are based on one shipbuilding industry only.

To the author's knowledge, this is the first empirical analysis on the implementation of SCOR metrics to the traditional shipbuilding industry. The analysis to improve the traditional shipbuilding supply chains performance can provide managerial insights to other industries.

This study aims to apply a Lean Six Sigma framework to support continuous improvement in the maritime industry (shipbuilding, logistics services and shipping companies) during COVID-19 pandemics. By applying the concepts of Lean Six Sigma and supply chain resilience, the most suitable continuous improvement method for the maritime industry is developed to maintain a resilient supply chain during COVID-19.

A specific shipbuilding, logistics services and shipping company in Indonesia is chosen as the research object. The Lean Six Sigma framework reveals the wastes through the supply chain resilience concept, and implements internal business processes to maintain optimal system performance.

The paper identifies important implementation aspects in applying Lean Six Sigma to shipbuilding, logistics services and shipping. The DMAIC (define, measure, analyze, improve and control) approach is applied to achieve supply chain resilience. Resilient measures are generated for the case companies to maximize performance during the pandemics.

This paper provides a new insight for integrating Lean Six Sigma and resilience strategies in the maritime industry during COVID-19 disruptions. The authors provide some insights to sustain the performance of the maritime industries under study.

This study is part of the first research in the maritime industry that focuses on continuous improvement during COVID-19 using Lean Six Sigma and supply chain resilience.

This paper aims to consider a sustainable inventory model with price dependent demand, non-instantaneous deterioration rate, discount facility, partially backlogged shortages and advance and delay in payments for a two-warehouse system.

This model considered a non-instantaneous deterioration, which starts after a certain period with a constant rate. The deterioration rate in the rented warehouse is more compared to own warehouse. The proposed model focused on two things. The first one is to the benefits of the advance payments strategy and delayed payment for the retailer and supplier, where the two-warehouse system is available and the second one is using an appropriate discount facility on no of the installment to maximize the total profit. The classical optimization technique is used to solve the problem.

The combination of trade-credits and advance payments is initiated to provide more benefits to the retailer. The findings prove that advance payments, which are received from the retailer to the supplier are beneficial for the supplier, who can influence the demand increase because of higher lower selling prices. Decreasing the selling price is used as a catalyst to increase demand. It also extends the discount concept of Khan et al. (2019, 2019b).

This model is limited by the fact that it does not consider variable deterioration. Therefore, the proposed inventory model could be extended by considering variable deterioration, as well as fully backlogged shortages and time-dependent demand function.

The study simultaneously considers a non-instantaneous deterioration inventory model, advance-payment, trade-credit for a sustainable two-warehouse inventory system. From the literature search to the best of knowledge no researcher has undergone this sort of study.