The Experts below are selected from a list of 506217 Experts worldwide ranked by ideXlab platform
Anil Kumar Dikshit - One of the best experts on this subject based on the ideXlab platform.
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interval valued facility Location Model an appraisal of municipal solid waste management system
Journal of Cleaner Production, 2018Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract This study presents an interval-valued facility Location Model to find economically best Locations for transfer stations under uncertainty. Transfer stations are the vital part of contemporary municipal solid waste management systems and economical siting of transfer stations using developed Model lead to a financially sustainable system. Often, the associated uncertainty of these systems cannot be Modeled by conventional probabilistic or fuzzy approaches under a data scarce scenario; however, Models based on interval analysis are found to be very effective in such cases. A set of univariate and multivariate sensitivity analyses adduces the need of uncertainty analysis for quantification and propagation of uncertainty. The demonstration of Model on city of Nashik (India) provides (i) economical feasibility, optimum capacity and economically best Locations of transfer stations; and (ii) impact of uncertain parameters on the best Locations. The developed Model felicitates a convenient decision-making to identify economically best Locations of transfer stations under uncertain environment.
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a facility Location Model for municipal solid waste management system under uncertain environment
Science of The Total Environment, 2017Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract In municipal solid waste management system, decision makers have to develop an insight into the processes namely, waste generation, collection, transportation, processing, and disposal methods. Many parameters ( e.g. , waste generation rate, functioning costs of facilities, transportation cost, and revenues) in this system are associated with uncertainties. Often, these uncertainties of parameters need to be Modeled under a situation of data scarcity for generating probability distribution function or membership function for stochastic mathematical programming or fuzzy mathematical programming respectively, with only information of extreme variations. Moreover, if uncertainties are ignored, then the problems like insufficient capacities of waste management facilities or improper utilization of available funds may be raised. To tackle uncertainties of these parameters in a more efficient manner an algorithm, based on interval analysis, has been developed. This algorithm is applied to find optimal solutions for a facility Location Model, which is formulated to select economically best Locations of transfer stations in a hypothetical urban center. Transfer stations are an integral part of contemporary municipal solid waste management systems, and economic siting of transfer stations ensures financial sustainability of this system. The Model is written in a mathematical programming language AMPL with KNITRO as a solver. The developed Model selects five economically best Locations out of ten potential Locations with an optimum overall cost of [394,836, 757,440] Rs. 1 /day ([5906, 11,331] USD/day) approximately. Further, the requirement of uncertainty Modeling is explained based on the results of sensitivity analysis.
Saman Hassanzadeh Amin - One of the best experts on this subject based on the ideXlab platform.
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a facility Location Model for global closed loop supply chain network design
Applied Mathematical Modelling, 2017Co-Authors: Saman Hassanzadeh Amin, Fazle BakiAbstract:Abstract Forward and reverse supply chains form a closed-loop supply chain. In this paper, a mathematical Model is proposed for a closed-loop supply chain network by considering global factors, including exchange rates and customs duties. The Model is a multi-objective mixed-integer linear programming Model under uncertain demand. A solution approach based on fuzzy programming is developed for solving the optimization problem. The Model is then applied in a network, which is located in Southwestern Ontario, Canada. A sensitivity analysis is provided to validate the Model. This Model considers global factors, multi-objectives, and uncertainty simultaneously in a closed-loop supply chain network.
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a multi objective facility Location Model for closed loop supply chain network under uncertain demand and return
Applied Mathematical Modelling, 2013Co-Authors: Saman Hassanzadeh Amin, Guoqing ZhangAbstract:Abstract A closed-loop supply chain (CLSC) network consists of both forward and reverse supply chains. In this paper, a CLSC network is investigated which includes multiple plants, collection centres, demand markets, and products. To this aim, a mixed-integer linear programming Model is proposed that minimizes the total cost. Besides, two test problems are examined. The Model is extended to consider environmental factors by weighed sums and e -constraint methods. In addition, we investigate the impact of demand and return uncertainties on the network configuration by stochastic programming (scenario-based). Computational results show that the Model can handle demand and return uncertainties, simultaneously.
A K Bhurjee - One of the best experts on this subject based on the ideXlab platform.
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interval valued facility Location Model an appraisal of municipal solid waste management system
Journal of Cleaner Production, 2018Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract This study presents an interval-valued facility Location Model to find economically best Locations for transfer stations under uncertainty. Transfer stations are the vital part of contemporary municipal solid waste management systems and economical siting of transfer stations using developed Model lead to a financially sustainable system. Often, the associated uncertainty of these systems cannot be Modeled by conventional probabilistic or fuzzy approaches under a data scarce scenario; however, Models based on interval analysis are found to be very effective in such cases. A set of univariate and multivariate sensitivity analyses adduces the need of uncertainty analysis for quantification and propagation of uncertainty. The demonstration of Model on city of Nashik (India) provides (i) economical feasibility, optimum capacity and economically best Locations of transfer stations; and (ii) impact of uncertain parameters on the best Locations. The developed Model felicitates a convenient decision-making to identify economically best Locations of transfer stations under uncertain environment.
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a facility Location Model for municipal solid waste management system under uncertain environment
Science of The Total Environment, 2017Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract In municipal solid waste management system, decision makers have to develop an insight into the processes namely, waste generation, collection, transportation, processing, and disposal methods. Many parameters ( e.g. , waste generation rate, functioning costs of facilities, transportation cost, and revenues) in this system are associated with uncertainties. Often, these uncertainties of parameters need to be Modeled under a situation of data scarcity for generating probability distribution function or membership function for stochastic mathematical programming or fuzzy mathematical programming respectively, with only information of extreme variations. Moreover, if uncertainties are ignored, then the problems like insufficient capacities of waste management facilities or improper utilization of available funds may be raised. To tackle uncertainties of these parameters in a more efficient manner an algorithm, based on interval analysis, has been developed. This algorithm is applied to find optimal solutions for a facility Location Model, which is formulated to select economically best Locations of transfer stations in a hypothetical urban center. Transfer stations are an integral part of contemporary municipal solid waste management systems, and economic siting of transfer stations ensures financial sustainability of this system. The Model is written in a mathematical programming language AMPL with KNITRO as a solver. The developed Model selects five economically best Locations out of ten potential Locations with an optimum overall cost of [394,836, 757,440] Rs. 1 /day ([5906, 11,331] USD/day) approximately. Further, the requirement of uncertainty Modeling is explained based on the results of sensitivity analysis.
Vinay Yadav - One of the best experts on this subject based on the ideXlab platform.
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interval valued facility Location Model an appraisal of municipal solid waste management system
Journal of Cleaner Production, 2018Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract This study presents an interval-valued facility Location Model to find economically best Locations for transfer stations under uncertainty. Transfer stations are the vital part of contemporary municipal solid waste management systems and economical siting of transfer stations using developed Model lead to a financially sustainable system. Often, the associated uncertainty of these systems cannot be Modeled by conventional probabilistic or fuzzy approaches under a data scarce scenario; however, Models based on interval analysis are found to be very effective in such cases. A set of univariate and multivariate sensitivity analyses adduces the need of uncertainty analysis for quantification and propagation of uncertainty. The demonstration of Model on city of Nashik (India) provides (i) economical feasibility, optimum capacity and economically best Locations of transfer stations; and (ii) impact of uncertain parameters on the best Locations. The developed Model felicitates a convenient decision-making to identify economically best Locations of transfer stations under uncertain environment.
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a facility Location Model for municipal solid waste management system under uncertain environment
Science of The Total Environment, 2017Co-Authors: Vinay Yadav, Subhankar Karmakar, Anil Kumar Dikshit, A K BhurjeeAbstract:Abstract In municipal solid waste management system, decision makers have to develop an insight into the processes namely, waste generation, collection, transportation, processing, and disposal methods. Many parameters ( e.g. , waste generation rate, functioning costs of facilities, transportation cost, and revenues) in this system are associated with uncertainties. Often, these uncertainties of parameters need to be Modeled under a situation of data scarcity for generating probability distribution function or membership function for stochastic mathematical programming or fuzzy mathematical programming respectively, with only information of extreme variations. Moreover, if uncertainties are ignored, then the problems like insufficient capacities of waste management facilities or improper utilization of available funds may be raised. To tackle uncertainties of these parameters in a more efficient manner an algorithm, based on interval analysis, has been developed. This algorithm is applied to find optimal solutions for a facility Location Model, which is formulated to select economically best Locations of transfer stations in a hypothetical urban center. Transfer stations are an integral part of contemporary municipal solid waste management systems, and economic siting of transfer stations ensures financial sustainability of this system. The Model is written in a mathematical programming language AMPL with KNITRO as a solver. The developed Model selects five economically best Locations out of ten potential Locations with an optimum overall cost of [394,836, 757,440] Rs. 1 /day ([5906, 11,331] USD/day) approximately. Further, the requirement of uncertainty Modeling is explained based on the results of sensitivity analysis.
Fazle Baki - One of the best experts on this subject based on the ideXlab platform.
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a facility Location Model for global closed loop supply chain network design
Applied Mathematical Modelling, 2017Co-Authors: Saman Hassanzadeh Amin, Fazle BakiAbstract:Abstract Forward and reverse supply chains form a closed-loop supply chain. In this paper, a mathematical Model is proposed for a closed-loop supply chain network by considering global factors, including exchange rates and customs duties. The Model is a multi-objective mixed-integer linear programming Model under uncertain demand. A solution approach based on fuzzy programming is developed for solving the optimization problem. The Model is then applied in a network, which is located in Southwestern Ontario, Canada. A sensitivity analysis is provided to validate the Model. This Model considers global factors, multi-objectives, and uncertainty simultaneously in a closed-loop supply chain network.
