Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation

Shekarabi, Seyed Ashkan Hoseini; Gharaei, Abolfazl; Karimi, Mostafa

doi:10.1080/23302674.2018.1435835

Cited by 54 publications

(29 citation statements)

References 59 publications

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“…However, a logistic regression model can explain the main influencing factors only in a specific period, and it is difficult to accurately simulate and predict long-term and dynamic change 50 . The optimization and improvement of models and algorithms must be further studied, and new algorithms, such as generalized cross decomposition 51 , generalized outer approximation 52 and selective maintenance scheduling with multiple maintenance actions 53 , can be introduced to solve complex nonlinear problems and improve the applicability and accuracy of simulation prediction. In the current study, we considered only four explanatory variables of driving factors, and some important natural and social factors, such as precipitation, meteorological disasters, geological structures, geological disasters, and functional types of urban blocks, may have been omitted.…”

Section: Rs Interpretation Algorithms Have Been Developed To Extract mentioning

confidence: 99%

Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Zhang

2020

Sci Rep

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Ecological land is a type of land that has considerable ecological value. Understanding the evolution of urban ecological land in Zhuhai, China, holds great significance for revealing the evolution of ecological land in the Dawan District of southern China. We explored the temporal and spatial variation in urban ecological land in Zhuhai using the transformation matrix, equivalent ecological land, landscape index and ecological land center of gravity migration methods. Multivariate logistic regression was used to analyze the mechanism of ecological land change, and a transition probability map of the ecological land in the study area was drawn. The results showed the following. (1) From 1991 to 2018, the area of ecological land in Zhuhai city continuously decreased, with a reduction in area of 274.8 km2, or 32.3%. Sharp changes mainly occurred from 1991 to 2000. (2) The ecological land in the study area has gradually become fragmented, and the degree of landscape heterogeneity has increased. Affected by the expansion of the outer edge of the city to the southwest and the construction of ecological land within the city, the center of gravity of the ecological land has shifted to the northeast by 1346 m. (3) The elevation, slope, distance from built-up land and growth rate of built-up land are important factors influencing the transformation of ecological land. In the future, rivers and shallow coastal waters, tidal flats, and grasslands in the study area have the highest probability of transformation. The Jinwan District and Xiangzhou District will face severe ecological land protection pressure. The method of spatial–temporal analysis of urban ecological land developed in this paper can be applied in similar studies on other cities, and the results obtained for Zhuhai, China, have reference value for future urban planning and ecological protection work.

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Section: Rs Interpretation Algorithms Have Been Developed To Extract mentioning

confidence: 99%

Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Zhang

2020

Sci Rep

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“…For instance, the authors in [30] created an MINLP problem to solve an optimal lot-sizing policy in the supply chain (SC) that has an essential role in companies applying SC management to their system, using OA. In [31], a new algorithm based on the OA algorithm was designed for the stochastic shortest-path problem, where path costs are a weighted sum of the expected cost and standard deviation cost.…”

Section: Outer Approximationmentioning

confidence: 99%

“…The structure of the battery charging station and the system behavior are illustrated in Figure 6. The MPC problem (17) with limited resource constraints can thus be employed in the management of battery charging, using the model given by Equation (30). Problem P, in order to demonstrate a practical application, can be recast as follows:…”

Section: Batteries Charging With Activation Constraintsmentioning

confidence: 99%

Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

et al. 2020

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The interconnection of dynamic subsystems that share limited resources are found in many applications, and the control of such systems of subsystems has fueled significant attention from scientists and engineers. For the operation of such systems, model predictive control (MPC) has become a popular technique, arguably for its ability to deal with complex dynamics and system constraints. The MPC algorithms found in the literature are mostly centralized, with a single controller receiving the signals and performing the computations of output signals. However, the distributed structure of such interconnected subsystems is not necessarily explored by standard MPC. To this end, this work proposes hierarchical decomposition to split the computations between a master problem (centralized component) and a set of decoupled subproblems (distributed components) with activation constraints, which brings about organizational flexibility and distributed computation. Two general methods are considered for hierarchical control and optimization, namely Benders decomposition and outer approximation. Results are reported from a numerical analysis of the decompositions and a simulated application to energy management, in which a limited source of energy is distributed among batteries of electric vehicles.

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“…In recent literature harmonic search (HS) algorithm,Invasive weed (IW) techniques were developed for solving these problems[. Most of these recent techniques were successful in implementation of complex ML, NP hard problems [10][11][12][13][14][15][16][17][18].But still there is a lot scope and requirement in find the optimal solution in with high computational efficiency. Here in this research paper our we presented a binary flower pollination algorithm to solve ML assembly structure.…”

Section: Introductionmentioning

confidence: 99%

Flower Pollination Algorithm for Multi Level Lot Sizing Optimization

V.V.D.Sahithi¹

2021

ITII

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In this competitive and constantly changing world, meeting the customer requirements within less time by providing less cost is extremely tricky task. This is only possible by optimizing all the different parameters in its life cycle. Here Optimizing the inventory plays a major role.Maintaining the exact amount of inventory, at proper place, in appropriate level is a challenging task for production managers. When we work on Multi level environments this problem becomes even more complex.So, to optimize this kind of problems we applied binary form of Flower Pollination algorithm to solve this complex problem. we solved different inventory lot sizing problems with this FP algorithm and compared the results with genetic algorithm and other algorithms. In all the scenarios our simulation results shown that FP algorithm is better than other algorithms.

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Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: generalised outer approximation

Cited by 54 publications

References 59 publications

Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Decompositions for MPC of Linear Dynamic Systems with Activation Constraints

Flower Pollination Algorithm for Multi Level Lot Sizing Optimization

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