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Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.

A mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.

The model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.

The authors confirm that this is an original paper and has not been published or under consideration in any other journal.

This paper proposes a two-level supply chain including suppliers and manufacturers. The purpose of this paper is to design a resilient fuzzy risk-averse supply portfolio selection approach with lead-time sensitive manufacturers under partial and complete supply facility disruption in addition to the operational risk of imprecise demand to minimize the mean-risk costs. This problem is analyzed for a risk-averse decision maker, and the authors use the conditional value-at-risk (CVaR) as a risk measure, which has particular applications in financial engineering.

The methodology of the current research includes two phases of conceptual model and mathematical model. In the conceptual model phase, a new supply portfolio selection problem is presented under disruption and operational risks for lead-time sensitive manufacturers and considers resilience strategies for risk-averse decision makers. In the mathematical model phase, the stages of risk-averse two-stage fuzzy-stochastic programming model are formulated according to the above conceptual model, which minimizes the mean-CVaR costs.

In this paper, several computational experiments were conducted with sensitivity analysis by GAMS (General algebraic modeling system) software to determine the efficiency and significance of the developed model. Results show that the sensitivity of manufacturers to the lead time as well as the occurrence of disruption and operational risks, significantly affect the structure of the supply portfolio selection; hence, manufacturers should be taken into account in the design of this problem.

The study proposes a new two-stage fuzzy-stochastic scenario-based mathematical programming model for the resilient supply portfolio selection for risk-averse decision-makers under disruption and operational risks. This model assumes that the manufacturers are sensitive to lead time, so the demand of manufacturers depends on the suppliers who provide them with services. To manage risks, this model also considers proactive (supplier fortification, pre-positioned emergency inventory) and reactive (revision of allocation decisions) resilience strategies.

This paper aims to minimize the mean-risk cost of sustainable and resilient supplier selection, order allocation and production scheduling (SS,OA&PS) problem under uncertainty of disruptions. The authors use conditional value at risk (CVaR) as a risk measure in optimizing the combined objective function of the total expected value and CVaR cost. A sustainable supply chain can create significant competitive advantages for companies through social justice, human rights and environmental progress. To control disruptions, the authors applied (proactive and reactive) resilient strategies. In this study, the authors combine resilience and social responsibility issues that lead to synergy in supply chain activities.

The present paper proposes a risk-averse two-stage mixed-integer stochastic programming model for sustainable and resilient SS,OA&PS problem under supply disruptions. In this decision-making process, determining the primary supplier portfolio according to the minimum sustainable-resilient score establishes the first-stage decisions. The recourse or second-stage decisions are: determining the amount of order allocation and scheduling of parts by each supplier, determining the reactive risk management strategies, determining the amount of order allocation and scheduling by each of reaction strategies and determining the number of products and scheduling of products on the planning time horizon. Uncertain parameters of this study are the start time of disruption, remaining capacity rate of suppliers and lead times associated with each reactive strategy.

In this paper, several numerical examples along with different sensitivity analyses (on risk parameters, minimum sustainable-resilience score of suppliers and shortage costs) were presented to evaluate the applicability of the proposed model. The results showed that the two-stage risk-averse stochastic mixed-integer programming model for designing the SS,OA&PS problem by considering economic and social aspects and resilience strategies is an effective and flexible tool and leads to optimal decisions with the least cost. In addition, the managerial insights obtained from this study are extracted and stated in Section 4.6.

This work proposes a risk-averse stochastic programming approach for a new multi-product sustainable and resilient SS,OA&PS problem. The planning horizon includes three periods before the disruption, during the disruption period and the recovery period. Other contributions of this work are: selecting the main supply portfolio based on the minimum score of sustainable-resilient criteria of suppliers, allocating and scheduling suppliers orders before and after disruptions, considering the balance constraint in receiving parts and using proactive and reactive risk management strategies simultaneously. Also, the scheduling of reactive strategies in different investment modes is applied to this problem.

Considering sustainability and resilience together is crucial in food supply chain (FSC) management, as it ensures a balanced approach that meets environmental, economic and social needs while maintaining the system's capacity to withstand disruptions. Towards this, a multi-objective optimisation model is proposed in this study to create an integrated sustainable and resilient FSC. The proposed model employs four objective functions – each representing a dimension of sustainability and one for resilience and utilises an augmented ϵ-constraint method for solving. The findings highlight the interplay between sustainability aspects and resilience, illustrating that overemphasis on any single dimension can adversely affect others. Further, the proposed model is applied to the case of Indian mango pulp supply chain and several inferences are derived. The proposed model would assist decision-makers in making a well-balanced choice based on sustainability and resilience considerations.

Trade-offs are unavoidable in a competitive and difficult economic environment, causing a challenge for those wanting to provide consistently high-quality service across all touchpoints in the service delivery ecosystem, included in which is the higher education (HE) sector. This study aims to explore the key factors influencing service trade-offs related to the efforts of academics in Malaysia’s HE sector.

A self-administered questionnaire was distributed to 400 full-time academics from several higher learning institutions in Malaysia. Data were analysed using the partial least squares-structural equation modelling (PLS-SEM) approach.

The results reveal that service trade-offs in the HE sector were heavily influenced by service priorities. Customisation of services, meeting individual student needs, working under immense pressure within tight timeframes and focusing on teaching and research jointly contribute to academics’ service trade-offs in the HE sector. Indeed, the nature of the job necessitates such trade-offs by default, as academics are unable to cancel or postpone classes due to scheduling constraints and the requirement to be physically present during class sessions.

HE administrators and managers should provide academics with adequate resources, effective work allocation and optimal timeframes for task completion, as service priorities are the key factors influencing service trade-offs in Malaysia’s HE sector. The satisfaction of these needs would enable academics’ service priorities and trade-offs to be better balanced, thereby contributing to better operational efficiency, boosting organisational performance and maintaining business sustainability.

The empirical results serve to clarify the key factors influencing service trade-offs in the HE sector, thus expanding the extant literature, which has mostly concentrated on describing the same phenomena in the manufacturing sector. The proposed service trade-offs model would serve as a guideline for operational efficiencies in the HE sector to prevent future recurrence and reduce the potential risk of service disruption, thus mitigating the risk of dissatisfaction.

The main purpose is to minimize the total inventory cost of chain, whereas the stochastic constraints are satisfied. In other words, the goal is to find optimum agreed stockpiles and period length for products to minimize the total inventory cost of the chain while the stochastic constraints are fulfilled.

This paper designs and optimizes an integrated inventory model in a four-echelon supply chain that contains a supplier, a producer, a wholesaler and multiple retailers. All four levels agree with each other to make an integrated inventory system. Products in this model have a multi-stage production process, and the model is bounded by multiple stochastic constraints. The problem model is nonlinear and large. So, the interior point method as an effective algorithm is used for solving the recent convex nonlinear model. Two numerical examples are solved to demonstrate the application of this methodology and to evaluate the performance of the proposed approach.

The findings showed the model is applicable for real-world supply chain problems in the cases that echelons are going to do executive external integration. Also, the Interior Point algorithm has a satisfactory performance and a high efficiency in terms of optimum solution for solving nonlinear and large models.

The authors designed and optimized the inventory cost in a four-level integrated supply chain in stochastic conditions. The new decision variables, number of chain levels, multi-products, stochastic constraints and multi-stage products in four-level integrated supply chain are other novelties of this paper. The authors provided an efficient algorithm for solving a large-scale and nonlinear model in this research, too.

This study aims to analyze the managerial levers previously considered in literature in the setting of the provision of primary care and community services (in particular for patients with long-term conditions being treated also at home) as well as those scarcely explored that could potentially be adopted in the future.

This study was a structured literature review. The authors retrieved papers, published from 2005–2020, from electronic databases (i.e. ABI/INFORM Complete, Jstor, PubMed and Scopus). Each selected paper was assigned to a framework category, and a thematic analysis was performed.

Topics scarcely explored in literature were related to logistics/supply chain, economic evaluations, performance management and customer satisfaction. Some papers embraced more than one management topic, confirming the multidisciplinary nature of territorial healthcare services. The majority of research, however, focused on only one aspect of primary care services, and a lack of an integrated view regarding the provision of those services emerged.

This study represents a first attempt to rationalize the fragmented body of knowledge on the topic of the provision of primary and community care services. This study enabled some light to be shed on the managerial levers already explored previously in literature and also identifies a number of trajectories for future research.

The pandemic has caused severe disruptions and significant losses in various industries. In particular, the nursing service industry has been greatly affected, leading to increased service costs and attrition of nursing service provider (NSP) residents. Although prior studies suggest that outsourcing may mitigate losses from disruptions, there still lacks a detailed analysis of whether and when to adopt such a disruption solution.

This study develops a two-period game-theoretical model to explore the impacts of demand and cost disruptions caused by the pandemic on NSPs’ operational strategies, suppliers’ strategy choices and equilibrium prices and demand.

The results present several novel managerial insights. First, we suggest that higher demand and cost disruptions decrease service demand, but do not necessarily prompt an NSP to outsource nursing services. Interestingly, we find that even when the service cost of the outsourcing strategy is low, the NSP may still insist on the in-house strategy. Additionally, the equilibrium strategy does not always result in lower prices and higher demand.

Our findings provide insightful takeaways for NSPs to cope with the pandemic in the nursing service industry. The results also offer theoretical support for other industries to recover from demand and cost disruptions.

Sustainability is one of the major factors in the way of creating new structures in historical contexts. The economic principle plays a very significant role in sustainability besides the environmental and social components. Tabriz Historic Bazaar that has been inscribed on the World Heritage list has witnessed various developments in its surrounding area over recent years. The purpose of this study is to analyze the infill structure indicators in this region in terms of economic sustainability.

First, based on related literature reviews and approaches, the indicators that should be considered in the creation of infill structures in historical contexts were collected. Later, by considering the vicinity zone of Tabriz Historic Bazaar, the effect of each indicator on the economic sustainability of the building was gathered by means of AHP questionnaires and in-person interviews with experts and analyzed by the Expert Choice software.

The findings present a guideline which indicates that the type of materials being used is the most important factor in order to create an economically sustainable infill structure in this setting. Accordance with the Climate of the region ranks second place and the Cultural land-use as the Suitable land use for this site goes for the third. The mentioned guideline includes 25 indicators and can help designers with a clear path.

This paper clarifies the order of indicators' importance for enhancing the design and consequently function of infill structures, being built in this historic context, with the aim of economic sustainability. The prioritization of indicators in this research depends mainly on their relevance to the conditions of the study area, but the methodology can be used helpfully in similar cases.