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The development of a decision support tool for the single‐period inventory problem is presented. The support tool allows a consideration of the following factors: empirical frequency distributions, theoretical probability distribution functions and managerial probability estimates of total demand over the period; piece‐wise linear (possibly discontinuous) cost functions. Such functions allow for the possibility of “fixed cost” elements and/or “economies/diseconomies” of scale and account for most, if not all, of the purchase cost, holding cost, salvage revenue and shortage cost functions that arise in practice; choice of performance measures; and “what‐if” analysis on the problem parameters. The support tool, which uses the Monte Carlo simulation option of Visual IFPS/Plus, is transparent and constructively simple and thus readily facilitates understanding, acceptance and implementation by management. The support tool runs under the Windows operating system and has easy access to appropriate spreadsheet and word‐processing packages for further processing and report presentation.

This paper aims to propose a supply model of periodic review with joint replenishment for multi-products grouped by several variables with random and time dependence demand.

The products are grouped by multivariate cluster analysis. The stochastic inventory model describes the random demand of each product, considering the temporal dependency through a generalized autoregressive moving average model. Stochastic programming for the total cost of inventory is obtained considering the expected value of the demand per unit of time.

The total costs for the products grouped with the proposed model are 6% lower than for the individual inventory policy. The expected shortage units decrease significantly in the proposed grouped model with temporary dependence. In addition, the proposal with temporary dependency has lower costs than when the independent and identically distributed demand is considered.

The proposed policy is exemplified with real-world data from a Chilean hospital, where the products (drugs) are segmented by grouping variables, forming clusters of drugs with homogeneous behavior within the groups and heterogeneous behavior between groups.

The purpose of this paper is to examine the impact of renewable energy on the power supply chain and to study whether the renewable generator or the power grid that purchases power from the power spot market is better when the actual generation of renewable energy is insufficient. The authors want to compare and analyze the different power supply chain operation modes and discuss the optimal mode selection for renewable energy generator and power grid in different situations.

This paper studies the grid-led price competition game in the power supply chain, in which the power grid as a leader decides the price of transmission and distribution, and generators determine the power grid price. The renewable energy power generator and the traditional energy power generator conduct a price competition game; on the other hand, the power grid and power generators conduct Stackelberg games. The authors analyze the power supply of single power generator and two power generators, respectively, and research on the situation that the renewable energy cannot be fully recharged when the actual power generation is insufficient.

The study finds that both renewable and traditional power grid prices decline as price sensitivity coefficient of demand and installed capacity of renewable energy generators increase. Power grid premium decreases as the price sensitivity coefficient of demand increases, but rises as the installed capacity of renewable energy generator increases. When there is a shortage of power, if the installed capacity of renewable energy is relatively small and price sensitivity coefficient of demand is relatively large, the grid purchases the power from power spot market and shares cost with renewable energy generators, leading to higher expected profits of the renewable energy generators. On the contrary, the renewable energy generators prefer to make up power shortage themselves. For the power grid, purchasing the power by the renewable energy generators when there is a power shortage can bring more utility to the power grid when the installed capacity of renewable energy is lower and the demand price sensitivity coefficient is higher. When the installed capacity of renewable energy is high and the price sensitivity coefficient of demand is moderate, or the installed capacity of renewable energy is moderate and the demand price sensitivity coefficient is high, a generator that simultaneously possesses two kinds of energy source will bring more utility to the power grid. If the installed capacity of renewable energy and the demand price sensitivity coefficient both are small or the installed capacity of renewable energy and the price sensitivity coefficient of demand both are large, the power grid prefers to purchase the power by itself when there is a power shortage.

The goal of our paper analysis is to explore the implications of the theoretical model and address the series of research questions regarding the impact of the renewable energy on the power supply chain. The results of this study have key implications for reality. This paper sheds light on the power supply chain operation mode selection, which can potentially be used for the renewable energy generators to choose their operating mode and can also help traditional energy generators and power grid enterprises maximize their utility. This paper also has some references for the government to formulate the corresponding renewable energy development policy.

This paper studies the power operation mode under the uncertainty of supply and demand, and compares the advantages and disadvantages of renewable energy generator that makes up the shortage or the power grid purchases the power from power spot market then shares cost with the renewable energy generator. This paper analyzes the power grid-led coordination problem in a power supply chain, compares and analyzes the price competition game model of single power generator and dual power generators, and compares the different risk preferences of power grid.

The purpose of this paper is to analyze the effects of supply chain coordination on inventory management while the retailer inventory cycle consists of a shortage period and the backorder rate linearly decreases as a function of shortage duration. It is intended to consider how on‐hand inventory and shortage durations are altered when the decisions are centralized.

Mathematical modelling of inventory costs for the retailer and the vendor is used to formulate objective functions. The vendor sets his inventory period as an integer multiple (n) of the retailer inventory cycle in which the integer multiple is a decision variable. Solution spaces of models are analyzed to determine two other decision variables including, on‐hand inventory duration and shortage length.

The integrated model consists of a unique pseudo convex area when (n) is fixed and as a result, there is a unique minimum point. Based on numerical examples and sensitivity analysis, in most situations coordinated inventory management reduces total costs of the supply chain and cost reduction rate increase at larger production rates.

This paper is a combination between production‐inventory models in two‐stage supply chains and partial backordering, which has appeared in single inventory models. To the best of the authors' knowledge, no mathematical model has yet been proposed. Moreover, the benefits of synchronization are analyzed through numerical examples.

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.

This paper deals with the combined management and design of a sustainable pharmaceutical supply chain network with considering recycling.

This paper first utilizes the analytical hierarchy process to select and rank green manufacturers. Second, the authors proposed a multi-objective nonlinear mathematical model to design a sustainable pharmaceutical supply chain network. The proposed model has been linearized and solved using the LP-metric method using GAMS software.

A real case study has been conducted in Iran. The results show that environmental and social issues can be improved while minimizing total costs.

Given the criticality and importance of drugs in human health and the importance of recycling in today's world, proper management and design of a sustainable drug supply chain are necessary. This study pays special attention to environmental issues by utilizing multi-criteria decision approaches and customer satisfaction.

The purpose of this paper is to extend a routing model so that it may be applied to a real case study of material deliveries involved in a development operation, typical of regular humanitarian logistics, and to explore the impact of variations in available logistic assets.

The introduced model is a conceptual evolution of the study recently presented. It concerns the resource allocation and vehicle routing decisions in the well-known Haitian case. Different scenarios are analyzed and a sensitivity analysis is provided. Constraints related to transportation resources in a complex environment, transportation vehicle capacities, and delivery time restrictions are here considered.

This research shows how the logistic assets characteristics and their availability affect the distribution system performances, in terms of total distribution cost and shortages.

The present work explores the last mile distribution problem by providing a case study to assist decision makers in making effective and efficient distribution across the last mile. The research focusses upon the distribution systems management coupled with material distribution modalities.

The purpose of this paper is to develop a conceptual framework of integrated supply chain model that can be used to measure, evaluate and monitor operational performance under dynamic and uncertain conditions.

The research methodology consists of two stages: configuration of a conceptual framework of integrated supply chain model linked with performance measures and illustration of the integrated supply chain model and delivery performance using a case of dairy industry. The integrated supply chain model is based on a unitary structuring technique and forms the basis for measuring and evaluating supply chain performance. Delivery performance with variation of demand (forecast and actual) is monitored using a fuzzy-based decision support system, based on three inputs: capacity utilization (influenced by production disruption), raw materials shortage and quality of dairy products.

Integration of supply chain components (materials, resources, operations, activities, suppliers, etc.) of key processes using unitary structuring approach enables information integration in real time for performance evaluation and monitoring in complex supply chain situations. In addition, real-time performance monitoring is recognized as being of great importance for supply chain management in responding to uncertainties inherent in the operational environment.

Implementation of an integrated model requires maintenance of supply chain components with all necessary data and information in a system environment such as enterprise resource planning.

The integrated model provides decision-makers with an overall view of supply chain components and direct links that need to be maintained for supply chain performance evaluation and monitoring. Wider adaptation and diffusion of the proposed model require further validation of the model and feasibility of implementation, using real-time data and information on selected performance measures.

Integration of supply chain components across supply chain processes directly linked with performance measures is a novel approach for effective supply chain performance evaluation and monitoring in complex supply chains under dynamic and uncertain conditions.

The purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.

In total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.

There are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.

Only peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.

Stress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.

The current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

This paper aims to explore the impact of Sharīʿah-compliant stocks on other investor risk preferences beyond the risk aversion, namely, prudence and temperance.

This paper uses the non-parametric model data envelopment analysis with the shortage function as a measure of performance. The model uses three specifications considering skewness and kurtosis that describe according to expected utility theory, prudence and temperance.

Results show that first, efficient portfolios consist mainly of conventional stocks in the three-model specification. Second, the skewness improvement is achieved only when considering conventional stocks while Sharīʿah-compliant assets do not exhibit any impact on the third moment. Finally, diversification through both conventional and Sharīʿah-compliant stocks does not lead to kurtosis reduction. Sharīʿah-compliant stocks in efficient portfolios are sensitive to return and risk solely, and hence, prudence and temperance as related to skewness and kurtosis measures can be ignored in optimal portfolio selection during normal market conditions.

Findings suggest the same conclusions for four Islamic screening methods; however, readers should be prudent due to the limited sample. Results show that Sharīʿah-compliant assets do not have an impact on higher-order moments optimal portfolio returns, and hence, question the commonly admitted assumption of non-normality return distributions at least for Sharīʿah-compliant stocks.

The research findings suggest that Islamic investor preferences are described only by return and risk along with Sharīʿah criteria for stock selection and portfolio allocation. Portfolio managers should not care about higher-order moments to manage Sharīʿah-compliant funds. The traditional mean-variance Markowitz framework will be sufficient for investment or allocation decision-making. Description of Sharīʿah-compliant portfolio returns with only the first two order moments gives such asset more resiliency to extreme events like a crisis.

This research is the first in literature exploring whether prudence and temperance defined by higher-order moments can be drivers, besides Sharīʿah criteria, in portfolio allocation decision-making. This study is unique in terms of methodology and application. It uses individual stock data on the Casablanca Stock Exchange.