The Experts below are selected from a list of 9270 Experts worldwide ranked by ideXlab platform
Kamlesh A Patel - One of the best experts on this subject based on the ideXlab platform.
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optimizing inventory and marketing policy for non instantaneous deteriorating items with generalized type deterioration and holding cost rates
Omega-international Journal of Management Science, 2013Co-Authors: Nita H Shah, Hardik N Soni, Kamlesh A PatelAbstract:This paper considers an inventory system with non-instantaneous deteriorating item in which demand rate is a function of advertisement of an item and selling price. This paper aids the retailer in maximizing the total profit by determining optimal inventory and marketing parameters. In contrast to previous inventory models, an arbitrary holding cost rate and arbitrary deterioration rate have been incorporated to provide general framework to the model. First, a mathematical model is formulated and then some useful theoretical results have been framed to characterize the optimal solutions. The necessary and sufficient conditions for the existence and uniqueness of the optimal solutions are also derived. An algorithm is designed to find the optimum solutions of the proposed model. Numerical examples are included to illustrate the Algorithmic Procedure and the effects of key parameters are studied to analyze the behavior of the model.
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optimal pricing and inventory policies for non instantaneous deteriorating items with permissible delay in payment fuzzy expected value model
International Journal of Industrial Engineering Computations, 2012Co-Authors: Hardik N Soni, Kamlesh A PatelAbstract:Article history: Received 25 October 2011 Accepted February, 3 2012 Available online 18 February 2012 This study investigates optimal pricing and inventory policies for non-instantaneous deteriorating items with permissible delay in payment. The demand rate is as known, continuous and differentiable function of price while holding cost rate, interest paid rate and interest earned rate are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Under these general assumptions, we first formulated a fuzzy expected value model (EVM) and then some useful theoretical results have been derived to characterize the optimal solutions. An efficient algorithm is designed to determine the optimal pricing and inventory policy for the proposed model. The Algorithmic Procedure is demonstrated by means of numerical examples. © 2012 Growing Science Ltd. All rights reserved
Gaute Tomas Einevoll - One of the best experts on this subject based on the ideXlab platform.
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MEArec: A Fast and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity
Neuroinformatics, 2020Co-Authors: Alessio Paolo Buccino, Gaute Tomas EinevollAbstract:When recording neural activity from extracellular electrodes, both in vivo and in vitro , spike sorting is a required and very important processing step that allows for identification of single neurons’ activity. Spike sorting is a complex Algorithmic Procedure, and in recent years many groups have attempted to tackle this problem, resulting in numerous methods and software packages. However, validation of spike sorting techniques is complicated. It is an inherently unsupervised problem and it is hard to find universal metrics to evaluate performance. Simultaneous recordings that combine extracellular and patch-clamp or juxtacellular techniques can provide ground-truth data to evaluate spike sorting methods. However, their utility is limited by the fact that only a few cells can be measured at the same time. Simulated ground-truth recordings can provide a powerful alternative mean to rank the performance of spike sorters. We present here MEArec , a Python-based software which permits flexible and fast simulation of extracellular recordings. MEArec allows users to generate extracellular signals on various customizable electrode designs and can replicate various problematic aspects for spike sorting, such as bursting, spatio-temporal overlapping events, and drifts. We expect MEArec will provide a common testbench for spike sorting development and evaluation, in which spike sorting developers can rapidly generate and evaluate the performance of their algorithms.
Hardik N Soni - One of the best experts on this subject based on the ideXlab platform.
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optimizing inventory and marketing policy for non instantaneous deteriorating items with generalized type deterioration and holding cost rates
Omega-international Journal of Management Science, 2013Co-Authors: Nita H Shah, Hardik N Soni, Kamlesh A PatelAbstract:This paper considers an inventory system with non-instantaneous deteriorating item in which demand rate is a function of advertisement of an item and selling price. This paper aids the retailer in maximizing the total profit by determining optimal inventory and marketing parameters. In contrast to previous inventory models, an arbitrary holding cost rate and arbitrary deterioration rate have been incorporated to provide general framework to the model. First, a mathematical model is formulated and then some useful theoretical results have been framed to characterize the optimal solutions. The necessary and sufficient conditions for the existence and uniqueness of the optimal solutions are also derived. An algorithm is designed to find the optimum solutions of the proposed model. Numerical examples are included to illustrate the Algorithmic Procedure and the effects of key parameters are studied to analyze the behavior of the model.
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optimal pricing and inventory policies for non instantaneous deteriorating items with permissible delay in payment fuzzy expected value model
International Journal of Industrial Engineering Computations, 2012Co-Authors: Hardik N Soni, Kamlesh A PatelAbstract:Article history: Received 25 October 2011 Accepted February, 3 2012 Available online 18 February 2012 This study investigates optimal pricing and inventory policies for non-instantaneous deteriorating items with permissible delay in payment. The demand rate is as known, continuous and differentiable function of price while holding cost rate, interest paid rate and interest earned rate are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Under these general assumptions, we first formulated a fuzzy expected value model (EVM) and then some useful theoretical results have been derived to characterize the optimal solutions. An efficient algorithm is designed to determine the optimal pricing and inventory policy for the proposed model. The Algorithmic Procedure is demonstrated by means of numerical examples. © 2012 Growing Science Ltd. All rights reserved
Efstratios N Pistikopoulos - One of the best experts on this subject based on the ideXlab platform.
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a branch and bound method for the solution of multiparametric mixed integer linear programming problems
Journal of Global Optimization, 2014Co-Authors: Richard Oberdieck, Martina Wittmannhohlbein, Efstratios N PistikopoulosAbstract:In this paper, we present a novel algorithm for the solution of multiparametric mixed integer linear programming (mp-MILP) problems that exhibit uncertain objective function coefficients and uncertain entries in the right-hand side constraint vector. The Algorithmic Procedure employs a branch and bound strategy that involves the solution of a multiparametric linear programming sub-problem at leaf nodes and appropriate comparison Procedures to update the tree. McCormick relaxation Procedures are employed to overcome the presence of bilinear terms in the model. The algorithm generates an envelope of parametric profiles, containing the optimal solution of the mp-MILP problem. The parameter space is partitioned into polyhedral convex critical regions. Two examples are presented to illustrate the steps of the proposed algorithm.
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On the global solution of multi-parametric mixed integer linear programming problems
Journal of Global Optimization, 2013Co-Authors: Martina Wittmann-hohlbein, Efstratios N PistikopoulosAbstract:This paper deals with the global solution of the general multi-parametric mixed integer linear programming problem with uncertainty in the entries of the constraint matrix, the right-hand side vector, and in the coefficients of the objective function. To derive the piecewise affine globally optimal solution, the steps of a multi-parametric branch-and-bound Procedure are outlined, where McCormick-type relaxations of bilinear terms are employed to construct suitable multi-parametric under- and overestimating problems. The alternative of embedding novel piecewise affine relaxations of bilinear terms in the proposed Algorithmic Procedure is also discussed.
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a two stage method for the approximate solution of general multiparametric mixed integer linear programming problems
Industrial & Engineering Chemistry Research, 2012Co-Authors: Martina Wittmannhohlbein, Efstratios N PistikopoulosAbstract:In this work, we focus on the approximate solution of multiparametric mixed-integer linear programming (mp-MILP) problems involving uncertainty in the objective function coefficients and in the entries of the constraint matrices and vectors. A two-stage Algorithmic Procedure is proposed. In the first stage, the model is partially immunized against uncertainty using the worst-case oriented approach which leads to a partially robust mp-MILP model, whereas in the second stage explicit solutions of the robust model are derived by applying a suitable multiparametric programming algorithm for mp-MILP problems. Computational studies are presented, demonstrating that the proposed two-stage robust optimization/multiparametric programming Procedure is computationally efficient and that it provides an upper bound on the overall solution of the general mp-MILP problem.
Alessio Paolo Buccino - One of the best experts on this subject based on the ideXlab platform.
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MEArec: A Fast and Customizable Testbench Simulator for Ground-truth Extracellular Spiking Activity
Neuroinformatics, 2020Co-Authors: Alessio Paolo Buccino, Gaute Tomas EinevollAbstract:When recording neural activity from extracellular electrodes, both in vivo and in vitro , spike sorting is a required and very important processing step that allows for identification of single neurons’ activity. Spike sorting is a complex Algorithmic Procedure, and in recent years many groups have attempted to tackle this problem, resulting in numerous methods and software packages. However, validation of spike sorting techniques is complicated. It is an inherently unsupervised problem and it is hard to find universal metrics to evaluate performance. Simultaneous recordings that combine extracellular and patch-clamp or juxtacellular techniques can provide ground-truth data to evaluate spike sorting methods. However, their utility is limited by the fact that only a few cells can be measured at the same time. Simulated ground-truth recordings can provide a powerful alternative mean to rank the performance of spike sorters. We present here MEArec , a Python-based software which permits flexible and fast simulation of extracellular recordings. MEArec allows users to generate extracellular signals on various customizable electrode designs and can replicate various problematic aspects for spike sorting, such as bursting, spatio-temporal overlapping events, and drifts. We expect MEArec will provide a common testbench for spike sorting development and evaluation, in which spike sorting developers can rapidly generate and evaluate the performance of their algorithms.