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The purpose of this paper is to maximize the average profit of the supply chain by calculating the order quantity, the number of shipments during the production time of the vendor, the number of shipments during the supply cycle of the vendor and the time when the retailer’s inventory level reaches to zero.

A production and inventory model for degrading commodities with stochastic demand and two-level partial trade credit in a supply chain is presented. The model’s applicability and the processes' feasibility for solving are verified by GAMS software with BARON.

The impact of the model’s parameters on the vendor and retailer’s average profit was found through sensitivity analysis. The effect of the model’s parameters on the supply chain’s average profit was also found. Moreover, the reasons for this effect were given.

First, decision-makers may use this model to increase the supply chain's average profit. Second, the proposed model takes a general form. Third, the policymakers can also adjust the model’s parameters according to their preferences to get the desired results.

First, this paper develops an inventory and production model for perishable goods. Second, it is believed that the demand is random because the demand is affected by many factors, which make the study more realistic. Third, this paper studies production and inventory problems from the supply chain perspective. Finally, the interest for partial trade credit is calculated. The interest caused by stochastic shortages is also considered and calculated.

In a multi‐item environment with a joint set‐up cost structure considerable savings may be realised by co‐ordinating the replenishments. This article presents a unified survey of the inventory control literature designed to capture the models that fit in this frame. In general these models are complex and require a great deal of computational effort to obtain an exact solution. The literature relies mainly on heuristic procedures.

A comprehensive review of the literature for the problem of lot‐size scheduling (serial and assembly) considering the uncapacitated problem and complicated capacitated assembly manufacturing structure. Analyses the different solution techniques and findings for each product set.

Some essential issues about modeling of reverse logistics (RL) systems and product recovery networks include consideration of the qualities of the returned products, taking into account uncertainty and integrating the forward and reverse flows. The purpose of this paper is to develop the integrated RL model, which focuses on the control of inventory and production planning problems in a case of uncertainty in demand, quantities and qualities of returns.

The model involves a forward production route, three alternative recovery routes and a disposal route. Various levels of qualities are considered for returned products. A fuzzy mixed integer programming model (FMIP) is developed to provide a solution for the problems of production planning and inventory control. After maximizing the satisfaction degree, different solutions can have the same maximum. Moreover, policies that use all recovery routes and reduce the overall uncertainty have no chance to be chosen. To tackle these problems, a two-phase approach method is applied.

According to the results of the numerical example, using different and appropriate recovery options based on the quality of returns can significantly decrease the recovery costs. Similarly, it is shown that the two-phase approach can be an effective and efficient method to reach a satisfactory solution for such problems.

In this study, after maximizing the FMIP model, a two-phase approach ‒ as a novel optimization technique in this research ‒ is employed to achieve a desirable solution.

The purpose of this study is to gain some insights into the number of shortages resulting from two alternative demand allocation schemes between a contractor (machine M₁) and subcontractor (machine M₂), on the one hand, and from inventory accumulation, on the other hand. The shortages stem from random machine breakdowns, and each machine undergoes preventive maintenance. The motivation behind inventory accumulation is to allow demand to be fulfilled even when both machines are down.

The number of shortages stemming from all scenarios under consideration was established via computer simulation with the Arena^© language.

For demand allocation that remains unchanged for the duration of the planning horizon and constant reliability of M₁, it was found that, the less reliable M₂ is, the more biased in favour of M₁ will be the optimal demand allocation and the greater will be the number of shortages. Moreover, both dynamic demand reallocation over the planning horizon and inventory accumulation result in a substantial reduction in shortages.

The results are representative of the specific data, which were assumed in the simulation models. Nevertheless, this methodology is recommended for this type of analysis, as it is highly flexible and can take into account many practical considerations, which an analytical approach cannot.

Within the context of unreliable production machines, the most important practical implication of this study is that the dynamic reallocation of demand between a contractor and subcontractor, along with inventory accumulation, both have the potential to yield important reductions in the number of shortages.

The subject‐matter of this paper was not previously reported in the literature. Furthermore, the insights gained as a result of this study can yield substantial benefits to companies in terms of improving their service levels as measured by reduced shortages.

Reverse supply chain (RSC) is one of the ways to handle product returns efficiently. Recovery of residual value from product returns also helps in achieving sustainability. Its successful implementation requires coordination among all the channel members involved in the activities, from the acquisition to collection to the disposition of returned products. This article aims to review the literature about coordination issues in the RSC.

A systematic literature review of 151 articles published during 2004–2021 is carried out. Theory, context and methodology (TCM) framework of the literature review is used to identify the research gaps for future research directions.

This study identifies the characteristics of RSC coordination. It includes channel structures; coordination mechanisms; performance measuring parameters; the methodology applied and explored industries. The review shows that game-theoretical modeling in RSC coordination is the most commonly used method to coordinate the channels. It was found that issues like disruption, fairness and corporate social responsibility are not explored in-depth and offer much potential for future research.

There are very limited studies on coordination issues in the RSC. The proposed articles add value by considering RSC issues from different strategic, government, consumers' behavior and functionality decision-making point of view.

Proposes that, due to the changing market, companies can no longer work with the logistic systems of the past but must develop new logistic concepts, logistic management and control systems to support the new concepts. Discusses the importance of order penetration point (OPP) within the development of time‐based management and control systems. Concludes that creativity in product development, production and distribution must be based on strong modern logistical foundations to survive in the competitive market.

Surveys multiple‐stage production planning literature to reveal that this sizeable body of research is largely inspired by single‐item production planning. Suggests several promising research opportunities, including the possible development of scheduling techniques not derived from older, single‐item procedures. Highlights the need for further comparative testing between existing “improved” techniques, as well as the wealth of work yet to be done in multiple‐stage production planning with limited resources and possible extensions to supply‐chain management.

This research proposes a decision framework for using non-financial measures to define a replenishment policy for perishable health products. These products are perishable and substitutable by nature and create complexities for managing inventory. Instead of a financial measure, numerous measures should be considered and balanced to meet business objectives and enhance inventory management.

This research applies a multi-methodological approach and develops a framework that integrates discrete event simulation (DES), analytic hierarchy process (AHP) and data envelopment analysis (DEA) techniques to define the most favourable replenishment policy using non-financial measures.

The integration framework performs well as illustrated in the numerical example; outcomes from the framework are comparable to those generated using a traditional, financial measures-based, approach. This research demonstrates that it is feasible to adopt non-financial performance measures to define a replenishment policy and evaluate performance.

The framework, thus, prioritises non-financial measures and addresses issues of lacking information sharing and employee involvement to enhance hospitals' performance while minimising costs. The non-financial measures improve cross-functional communication while supporting simpler transformations from high-level strategies to daily operational targets.

The objective of this work is to develop a model that can be used for simulation of different parameters including price, subjected to different control strategies.

The entire supply chain can be modelled by combining the transfer function into a closed loop system. The transfer function of each entity in the supply chain can be obtained by using the control theory tools. The model can be approximated as a linear discrete system with various operating constants, like lead time, price, order policy and supply.

The continuous replenishment ordering policy for a distribution node in a supply chain was analyzed using the z-transform. Characteristic equations of the closed loop transfer function are obtained. The bullwhip (BW) effect is analyzed. Study proves that the BW effect is in evitable if the standard heuristic ordering policy is employed with demand forecasting; also the paper analysed price supply trade-off for dynamic demand and supply. Simulation results show that BW is less in PI and simple p-only with cascade control. Robust control and PD, PID control results are not shown in this literature, and it is subject to further research.

Research is original, it can be applicable in today's dynamic world, due to globalization, it is necessary to have a automated machine that can handle most of supply chain decision.