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This paper is closed access until 11th September 2019. ; The closed-loop supply chain (CLSC) management as one of the most significant management issues has been increasingly spotlighted by the government, companies and customers, over the past years. The primary reasons for this growing attention mainly down to the governments-driven and environmental-related regulations which has caused the overall supply cost to reduce while enhancing the customer satisfaction. Thereby, in the present study, efforts have been made to propose a facility location/allocation model for a multi-echelon multi-product multi-period CLSC network under shortage, uncertainty, and discount on the purchase of raw materials. To design the network, a mixed-integer nonlinear programming (MINLP) model capable of reducing total costs of network is proposed. Moreover, the model is developed using a robust fuzzy programming (RFP) to investigate the effects of uncertainty parameters including customer demand, fraction of returned products, transportation costs, the price of raw materials, and shortage costs. As the developed model was NP-hard, a novel whale optimization algorithm (WOA) aimed at minimizing the network total costs with application of a modified priority-based encoding procedure is proposed. To validate the model and effectiveness of the proposed algorithm, some quantitative experiments were designed and solved by an optimization solver package and the proposed algorithm. Comparison of the outcomes provided by the proposed algorithm and exact solution is indicative of high quality performance of the applied algorithm to find a near-optimal solution within the reasonable computational time.

Cash-based interventions (CBIs) as one form of aid have recently received substantial interest from humanitarian organizations in persistent humanitarian crises. This article proposes a system dynamics (SD) approach to study the CBIs' impact factors on all aspects of the beneficiaries' dignity in longstanding refugee crises, such as the case of Syrian refugees in Turkey. Reviewing the humanitarian management literature, we first develop a set of holistic causal loops to better understand the building boxes of refugees' dignity and their interactions. Then, an SD model is proposed and calibrated by field data from humanitarian organizations. The result of CBI amount sensitivity and payment time periods shows that CBIs are significantly more effective in diminishing child labor rates and to improve in health and accommodation service reception by the refugees in short terms, but to be as much effective in longer terms, humanitarian organizations must be more directly contribute to service capacity-building activities that are strategies by the hosting governments and supported by the international bodies, such as EU and UN. Otherwise, long-term or enhanced CBI supports can only lead to accelerated service capacity saturation and thus put extra pressure on already strained services and cause tensions between hosting and refugee communities.