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This paper presents bi-level decision making models for advertising planning problem. Advertising planning process consists of multiple objectives and is generally decentralised involving various hierarchical levels of decision making. Considering the cost and impact related factors, long and short duration ads for a single product are made for telecasting. The models presented in the paper are designed so as to allocate the number of advertisements of each kind to different channels under different time zones of a day with the objectives of maximization of ads impact and minimization of net cost at two different levels. We present two models based on minimum impact value to be achieved by advertisement as a constraint considering that the budget available for advertising is uncertain. We extend and present a solution approach developed for fuzzy bi-level integer decision making model with fuzzy constraints. Finally, we provide a numerical illustration to discuss the applicability of the proposed models.

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Purpose This paper aims to develop a grey decentralized bi-level multi-objective programming (MOP) model. A solution approach is also proposed for the given model. A production and transportation plan for a closed loop supply chain network under an uncertain environment and different scenarios is also developed. Design/methodology/approach In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using GLP. Membership functions for the decision variables under the control of the leader and for the goals are created. These membership functions are then used to generate the final solutions. Findings This paper provides insight for fomenting the decision-making process while providing a more flexible approach in uncertain logistics problems. The deviations of the final solution from the individual best solutions of the two levels are very little. These deviations can further be reduced by adjusting the tolerances associated with the decision variables under the control of the leader. Practical implications The proposed approach uses the concept of membership functions of linear form, and thus, requires less computational efforts while providing effective results. Most of the organizations exhibit decentralized decision-making under the presence of uncertainties. Therefore, the present study is helpful in dealing with such scenarios. Originality/value This is the first time, formulation of a decentralized bi-level multi-objective model under a grey environment is carried out as per the best knowledge of the authors. A solution approach is developed for bi-level MOP under grey uncertainty.

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Purpose The continual onset of natural and manmade disasters propels the humanitarian supply chain (HSC) efforts (by organizations, groups and individuals) to always be on a stand-by mode with more and more sustainable solutions. Despite all the sincere and coordinated efforts from all the humanitarian agents and bodies, the likely sustainable outputs are hampered by certain barriers (impediments) which exist at different levels of the HSCs. A better understanding of such barriers and their mutual relationship is deemed helpful in improving the outcomes of humanitarian efforts. Thus, the purpose of this paper is to explore, refine, establish and classify these barriers which thwart the sustainable efforts of the HSCs individually as well as collectively. Design/methodology/approach An extensive literature review is conducted to identify these barriers which were followed by soliciting the experts’ inputs to update, refine and retain the contextually relevant ones. The opinions about the nine identified and refined barriers are taken from eight experts based in the Northern India who are having at least five years of experience in humanitarian operations. Fuzzy interpretive structural modeling (FISM) is used to examine and establish a hierarchical relationship among these barriers, whereas fuzzy Matrice d’impacts croisés multiplication appliquée á un classment analysis is carried out to further classify these barriers into dependent, autonomous, linkage and dependent barriers. Findings The analysis led to the formation of a FISM model where the operational challenges affecting the performance occupy the topmost position in the hierarchy. The results reveal that inconsistent motives, coordination and communication and operational challenges affecting the performance are the dependent, poor strategic planning, capacity-related challenges and poor performance measurement system are the autonomous, and financial challenges, locational challenges and lack of proper awareness are the independent barriers. Research limitations/implications The focus of the researchers was to study and examine these barriers to sustainable HSCs with special reference to the epidemics and pandemics (especially COVID-19), and it sheds light particularly arising during and post disaster phases. Practical implications The structural model contributed by this study is expected to be meaningful for practitioners besides enriching the body of literature. In the context of pandemics, it distinguishes itself from the other available frameworks. Social implications As this research has been carried out in the context of the novel COVID-19, the framework is expected to assist policymakers in comprehending the issues impeding the sustainability of noble humanitarian efforts. Thus, ultimately it is expected to contribute to the ultimate cause of society at large. Originality/value This research endeavor distinguishes itself from the other accessible published resources in terms of the specific context, the methodological approach and the nature of respondents. This paper concludes with the practical implications and directions for future research.

Multicriteria mathematical modeling is an analytical framework for formally describing real‐life problems involving multiple and conflicting objectives. In the past decade, multicriteria decision‐making techniques have been applied in almost every area of the decision‐making including energy‐economic planning and sustainable development. Various mathematical and analytical models have been presented for the sustainable development planning and their assessment. In this paper, we discuss an approach related to multicriteria decision‐making and apply it for the assessment of the sustainable development goals of India by the year 2030. In the INDC report submitted to United Nations Framework Convention on Climate Change (2015, http://www4.unfccc.int/submissions/INDC/Published%20Documents/India/1/INDIA%20INDC%20TO%20UNFCCC.pdf), India has identified many goals related to the sustainable development like energy consumption, greenhouse gas emissions, GVA growth, and an increase in the employment by the year 2030. This paper overcomes the energy resource allocation problem in related literature due to the lack of sectorial data for the same year by calculating the estimates for each sector for the year 2030. We presented a multicriteria decision‐making model which allocates public labor force in the key economic sectors of India. The presented model is validated with the data of the key economic sectors and their contribution in the identified goals. The paper provides a decision support for the better management of future sustainable policies by assessing the efficiencies of the current policies toward future sustainable goals. We evaluated the identified goals using the multicriteria decision‐making approaches so that the strategic planning can be implemented by the policy makers and to present a quantitative justification of planning strategies.

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