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Article
Publication date: 26 September 2023

Seyed Mojtaba Taghavi, Vahidreza Ghezavati, Hadi Mohammadi Bidhandi and Seyed Mohammad Javad Mirzapour Al-e-Hashem

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…

342

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

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Article
Publication date: 8 October 2018

Mojtaba Moradi, Ashkan Hafezalkotob and Vahidreza Ghezavati

This study considers a project scheduling model to assess the project risks and the impacts on project sustainability when subcontractors collaborate under uncertainty. Moreover…

778

Abstract

Purpose

This study considers a project scheduling model to assess the project risks and the impacts on project sustainability when subcontractors collaborate under uncertainty. Moreover, some allocation methods are applied for fair allocating utility of the project and supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is considered in risk assessment in all coalitions.

Design/methodology/approach

The proposed mathematical programming model evaluates project risks when the subcontractors cooperate with each other by sharing their limited resources. Then, some cooperative game theory methods are applied for fair allocation of net present value, of the cooperation and finally sustainability aspects (economic, social and environmental) are investigated in risk assessment for each possible coalition.

Finding

The results of the proposed model indicate that the subcontractors can increase their profit by 10 per cent ($14,028,450 thousand) and save the equilibrium between sustainability aspects especially in grand coalition. It means that subcontractors do not have incentive to leave the coalition and the supper-additive property is feasible. Furthermore, risk assessment shows that project risks have less impact on subcontractor profits when they cooperate with each other.

Originality/value

Sustainability aspects may be investigated in project management in previous studies, but the authors study sustainability indicators when subcontractors form a coalition and share their resources in response to the risks of availability to resources and delay in completing the project under uncertainty.

Details

Kybernetes, vol. 48 no. 3
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 24 August 2022

Amir Khiabani, Alireza Rashidi Komijan, Vahidreza Ghezavati and Hadi Mohammadi Bidhandi

Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling…

291

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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

Details

Journal of Modelling in Management, vol. 18 no. 6
Type: Research Article
ISSN: 1746-5664

Keywords

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Article
Publication date: 6 September 2021

Bahareh Shafipour-Omrani, Alireza Rashidi Komijan, Seyed Jafar Sadjadi, Kaveh Khalili-Damghani and Vahidreza Ghezavati

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day…

227

Abstract

Purpose

One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day pairings can be generated in a single model. The flexibility in generating parings causes that the proposed model leads to better solutions compared to existing models. Another advantage of the model is minimizing the risk of COVID-19 by limitation of daily flights as well as elapsed time minimization. As airports are among high risk places in COVID-19 pandemic, minimization of infection risk is considered in this model for the first time. Genetic algorithm is used as the solution approach, and its efficiency is compared to GAMS in small and medium-size problems.

Design/methodology/approach

One of the most complex issues in airlines is crew scheduling problem which is divided into two subproblems: crew pairing problem (CPP) and crew rostering problem (CRP). Generating crew pairings is a tremendous and exhausting task as millions of pairings may be generated for an airline. Moreover, crew cost has the largest share in total cost of airlines after fuel cost. As a result, crew scheduling with the aim of cost minimization is one of the most important issues in airlines. In this paper, a new bi-objective mixed integer programming model is proposed to generate pairings in such a way that deadhead cost, crew cost and the risk of COVID-19 are minimized.

Findings

The proposed model is applied for domestic flights of Iran Air airline. The results of the study indicate that genetic algorithm solutions have only 0.414 and 0.380 gap on average to optimum values of the first and the second objective functions, respectively. Due to the flexibility of the proposed model, it improves solutions resulted from existing models with fixed-duty pairings. Crew cost is decreased by 12.82, 24.72, 4.05 and 14.86% compared to one-duty to four-duty models. In detail, crew salary is improved by 12.85, 24.64, 4.07 and 14.91% and deadhead cost is decreased by 11.87, 26.98, 3.27, and 13.35% compared to one-duty to four-duty models, respectively.

Originality/value

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

Details

Kybernetes, vol. 51 no. 12
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 11 January 2022

Seyedehanahita Mousavi, Ashkan Hafezalkotob, Vahidreza Ghezavati and Farshid Abdi

This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.

379

Abstract

Purpose

This study aims to identify and accurately assess the risk factors of competitors’ cooperation in the NPD project.

Design/methodology/approach

New product development (NPD) is essential to the survival of companies and surpassing other competitors. A key prerequisite for the success of an NPD project is the timing of new product delivery to the market. The main challenge faced by many project managers is the delay in execution and completion phases due to the complex nature and uncertainty of these projects. Rival companies' cooperation reduces the time spent on an NPD project which is an excellent way to reduce the risk of losing the market, but it increases other risk factors.

Findings

Based on the results, the security and confidentiality of innovation, the competitors attracting human resources and the company’s brand credibility factors were ranked higher than other factors and should be predicted and managed before cooperating with competitors.

Originality/value

This paper proposed a new model to assess risk factors in cooperation with rival companies in NPD projects. This model takes into account new parameters, for example, negative and positive risks, negative and positive passable risks and risk-based multi-objective optimization by ratio analysis plus full multiplicative form methodology for the rival companies cooperation in NPD projects. To evaluate the efficiency of the proposed model, a real case of the R&D unit of Iran Khodro Company was studied.

Details

Journal of Business & Industrial Marketing, vol. 37 no. 11
Type: Research Article
ISSN: 0885-8624

Keywords

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