The Experts below are selected from a list of 121872 Experts worldwide ranked by ideXlab platform
Armin Jabbarzadeh - One of the best experts on this subject based on the ideXlab platform.
-
sustainable design of a municipal solid waste management system considering waste separators a Real World Application
Sustainable Cities and Society, 2019Co-Authors: Razieh Heidari, Reza Yazdanparast, Armin JabbarzadehAbstract:Abstract Enhancing sustainability in Municipal Solid Waste (MSW) management requires options that alleviate environmental issues and provide economic and social benefits. Though, the social aspect of sustainability has not been thoroughly investigated in the related literature. Therefore, this paper proposes a new multi-objective mathematical programming model considering new employment opportunities as the social side of sustainability. Furthermore, due to ineffective public participation in the waste management processes in the developing countries, incorporating waste separation after collection in the waste management practices is the suggestion of this study to contribute to the social sustainability. Other aspect of the proposed model is uncertainty that is inevitable and should be acknowledged to guarantee reliability in the decision-making process. To handle the uncertain model coefficients and stipulations, we utilize the robust possibilistic programming approach. The Application of the proposed model is demonstrated in a Real case study associated with the Tehran MSW system. The obtained results indicate that composting is the worst waste final disposal alternative, while anaerobic digestion and incineration have better performance in terms of the sustainability indicators. Moreover, the preliminary findings of a sensitivity analysis show that the waste recovery percentage has a direct influence on rates of waste reuse and recycling.
-
closed loop supply chain network design under disruption risks a robust approach with Real World Application
Computers & Industrial Engineering, 2018Co-Authors: Armin Jabbarzadeh, Michael Haughton, Amir KhosrojerdiAbstract:Abstract In today’s globalized and highly uncertain business environments, supply chains have become more vulnerable to disruptions. This paper presents a stochastic robust optimization model for the design of a closed-loop supply chain network that performs resiliently in the face of disruptions. The proposed model is capable of considering lateral transshipment as a reactive strategy to cope with operational and disruption risks. The objective is to determine facility location decisions and lateral transshipment quantities that minimize the total supply chain cost across different disruption scenarios. A Lagrangian relaxation algorithm is developed to solve the robust model efficiently. Important managerial insights are obtained from the model implementation in a case study of glass the industry.
-
Robust supply chain network design: an optimization model with Real World Application
Annals of Operations Research, 2017Co-Authors: Shiva Zokaee, Behnam Fahimnia, Armin Jabbarzadeh, Seyed Jafar SadjadiAbstract:This paper presents a robust optimization model for the design of a supply chain facing uncertainty in demand, supply capacity and major cost data including transportation and shortage cost parameters. We first present a base model that aims to determine the strategic ‘location’ and tactical ‘allocation’ decisions for a deterministic four-tier supply chain. The model is then extended to incorporate uncertainty in key input parameters using a robust optimization approach that can overcome the limitations of scenario-based solution methods in a tractable way, i.e. without excessive changes in complexity of the underlying base deterministic model. The Application of the approach is investigated in an actual case study where Real data is utilized to design a bread supply chain network. Numerical results obtained from model implementation and sensitivity analysis experiments arrive at important managerial insights and practical implications.
Salvatore Greco - One of the best experts on this subject based on the ideXlab platform.
-
preference disaggregation method for value based multi decision sorting problems with a Real World Application in nanotechnology
Knowledge Based Systems, 2021Co-Authors: Milosz Kadzinski, Salvatore Greco, Krzysztof Martyn, Marco Cinelli, Roman Slowinski, Salvatore CorrenteAbstract:Abstract We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.
-
on the choquet multiple criteria preference aggregation model theoretical and practical insights from a Real World Application
European Journal of Operational Research, 2018Co-Authors: Marta Carla Bottero, Salvatore Greco, Valentina Ferretti, José Rui FigueiraAbstract:Abstract We consider the use of the Choquet integral for evaluating projects or actions in a Real-World Application starting from the case of the re-qualification of an abandoned quarry. Despite the Choquet integral being a very well-known preference model for which there is a rich and well developed theory, its Application in a multiple criteria decision aiding perspective requires some specific methodological developments. This led us to work out and implement in practice two new procedures: a first procedure to build interval scales with the objective of assigning utility values on a common scale to the criteria performances, and a second one to construct a ratio scale for assigning numerical values to the capacities of the Choquet integral. This article discusses the strengths and weaknesses of the Choquet integral as appearing in the case study, proposing as well insights related to the interaction of the experts within a focus group.
Reza Tavakkolimoghaddam - One of the best experts on this subject based on the ideXlab platform.
-
reliable blood supply chain network design with facility disruption a Real World Application
Engineering Applications of Artificial Intelligence, 2020Co-Authors: Nazanin Haghjoo, Reza Tavakkolimoghaddam, Hani Shahmoradimoghadam, Yaser RahimiAbstract:Abstract The blood supply of hospitals in disasters is a crucial issue in supply chain management. In this paper, a dynamic robust location–allocation model is presented for designing a blood supply chain network under facility disruption risks and uncertainty in a disaster situation. A scenario-based robust approach is adapted to the model to tackle the inherent uncertainty of the problem, such as a great deal of a periodic variation in demands and facilities disruptions. It is considered that the effect of disruption in facilities depends on the initial investment level for opening them, which are affected by the allocated budget. The usage of the model is implemented by a Real-World case example that addresses the demand and disruption probability as uncertain parameters. For large-scale problems, two meta-heuristic algorithms, namely the self-adaptive imperialist competitive algorithm and invasive weed optimization, are presented to solve the model. Furthermore, several numerical examples of managerial insights are evaluated.
Yaser Rahimi - One of the best experts on this subject based on the ideXlab platform.
-
reliable blood supply chain network design with facility disruption a Real World Application
Engineering Applications of Artificial Intelligence, 2020Co-Authors: Nazanin Haghjoo, Reza Tavakkolimoghaddam, Hani Shahmoradimoghadam, Yaser RahimiAbstract:Abstract The blood supply of hospitals in disasters is a crucial issue in supply chain management. In this paper, a dynamic robust location–allocation model is presented for designing a blood supply chain network under facility disruption risks and uncertainty in a disaster situation. A scenario-based robust approach is adapted to the model to tackle the inherent uncertainty of the problem, such as a great deal of a periodic variation in demands and facilities disruptions. It is considered that the effect of disruption in facilities depends on the initial investment level for opening them, which are affected by the allocated budget. The usage of the model is implemented by a Real-World case example that addresses the demand and disruption probability as uncertain parameters. For large-scale problems, two meta-heuristic algorithms, namely the self-adaptive imperialist competitive algorithm and invasive weed optimization, are presented to solve the model. Furthermore, several numerical examples of managerial insights are evaluated.
Ata Allah Taleizadeh - One of the best experts on this subject based on the ideXlab platform.
-
designing a resilient competitive supply chain network under disruption risks a Real World Application
Transportation Research Part E-logistics and Transportation Review, 2018Co-Authors: Ali Ghavamifar, Ahmad Makui, Ata Allah TaleizadehAbstract:Abstract We address an intra-supply chain competition where a producer and resellers competing to achieve their goals, while taking into consideration the uncertainties and disruption risks. We utilize a bi-level multi-objective programming approach for designing a competitive supply chain network. A hybrid solution approach, combining the compromise programming and Benders decomposition methods, is developed to solve the model. Furthermore, an efficient inequality constraint is proposed to cope with the computational complexity of the bi-level model. To explore the practical Application of the model, a Real-World case example is discussed. Finally, the scalability of the solution approach is illustrated for large-scale problems.
