Stochastic dynamic lot-sizing problem using bi-level programming base on artificial intelligence techniques

Wong, Jui-Tsung; Su, Chwen-Tzeng; Wang, Chun-Hsien

doi:10.1016/j.apm.2011.08.017

Cited by 16 publications

(8 citation statements)

References 30 publications

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“…A bilevel programming problem is a special MLP that bilcontains decision makers (DMs) in two levels. Bilevel programming has been used in water exchange in eco-industrial parks [23], manufacturer-retailer supply chain problems [24], and lot-sizing problems [25]. Considering a water resources allocation problem that involves multisources and multiusers, Lv et al [26] developed an interval fuzzy bilevel approach (IFBP) to solve the problems, from which decision makers had a characteristic of hierarchy and conflicted with each other.…”

Section: Introductionmentioning

confidence: 99%

Bilevel Multiobjective Programming Applied to Water Resources Allocation

Fang

Guo

et al. 2013

Mathematical Problems in Engineering

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Water allocation is an essential programming to support the sustainable development of Wuwei Basin, Gansu Province, China. To satisfy the demands of the decision makers (DMs) of each subarea and the total area, a bilevel multiobjective linear programming (BLMOLP) model is proposed. In the BLMOLP, DMs have a hierarchy of two levels—the upper level and the lower level DMs. In this paper, a fuzzy goal programming (FGP) approach is applied to solve the BLMOLP. Firstly, the upper level is solved and used as the tolerance for the lower level. Then the weights of each objective function in the lower level are evaluated. Finally, a satisfied optimization solution of the problem was calculated. The result suggests that the FGP is a simple and feasible approach to BLMOLP problems. The proposed method was applied to a case study for water resources allocation in Wuwei Basin. For four scenarios under consideration, the model can effectively balance the benefits among all regions and sections according to the priority of the upper level decision makers. The results indicate that comprehensive solutions have been obtained.

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Section: Introductionmentioning

confidence: 99%

Bilevel Multiobjective Programming Applied to Water Resources Allocation

Fang

Guo

et al. 2013

Mathematical Problems in Engineering

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“…Because of uneven distribution of water and changing environment, the key problem is to reallocate the limited water resources to competing water usage sectors while maintaining a system balance that maximizes the overall efficiency and minimizes each sector's vulnerability. In contrast to the traditional two-stage optimization model, stochastic dynamic programming Zeng et al (2017); Wong et al (2012), and multi-objective programming Madani (2011), this study considers a strategic interaction from the hierarchical perspective, which helps to solve different kinds of conflicts existing in water resources management systems. At present, there is very little literature on irrigation districts taking blue/virtual water transfers and water allocation into consideration within a bilevel framework at the same time.…”

Section: Global Modelmentioning

confidence: 99%

“…In regard to a solution, Eichfelder (2010) presented several new theoretical results for general multi-objective bilevel optimization problems using the optimistic approach. In other studies, different methods, such as particle swarm optimization and artificial neural networks, have been used to solve bilevel decision-making problems in water exchange in eco-industrial parks (Ramos, 2016), product engineering (Liu et al, 2017b), and lot-sizing problems (Wong et al, 2012). However, these techniques have seldom been applied to practical cases for the allocation of water resources due to their complexity.…”

Section: Introductionmentioning

confidence: 99%

A novel data-driven analytical framework on hierarchical water allocation integrated with blue and virtual water transfers

Yao¹,

Xu²,

Wu³

et al. 2019

Preprint

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Abstract. This study proposes a novel data-driven analytical framework to determine optimal allocation and conjunctive strategies of blue and virtual water transfers in the presence of different hydrological and economic conditions. Due to the water scarcity and uneven distribution, a Stackelberg–Nash–Harsanyi equilibrium model is developed to cope with the hierarchical conflict between the water affairs bureau and multiple water usage sectors. Results show that coalitional strategy of blue and virtual water transfers can substantially save water and improve utilization efficiency without harming sectors' benefits and increasing ecological stresses. Under various polices, we use data-driven analysis to simulate hydrological and economic parameters, such as available water, crop import price, water market price etc. Different results obtained through adjusting hydrological and economic parameters show that the optimal allocation and transfer strategy is more sensitive to hydrological factor instead of economic factor. Moreover, the results prove that conjunctive blue/virtual water transfers can response to market fluctuation. Ultimately, the proposed framework can achieve a sustainable management for physical and virtual water supply system under future hydrological and economic uncertainty.

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“…Hu et al [ 38 ] developed a multi-objective bi-level model for Qujiang River basin of China with the upper level DMs reflecting the river basin authority’s allocation principle of equity and stability and the lower level DMs aimed at ensuring maximal economic benefit efficiency for each subarea. In other studies, different methods such as Stackelberg game theory, particle swarm optimization and artificial neural network have been used to solve the bi-level decision making problems in water exchange in eco-industrial parks [ 39 ], manufacturer-retailer supply chain problems [ 40 ], and lot-sizing problems [ 41 ], respectively. However, these techniques have seldom been applied to practical cases for the allocation of water resources because of their complexity.…”

Section: Introductionmentioning

confidence: 99%

A linear bi-level multi-objective program for optimal allocation of water resources

et al. 2018

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This paper presents a simple bi-level multi-objective linear program (BLMOLP) with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader) in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers) in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON) technique which creates a compromise between upper and lower level decision makers (DMs), and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

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Stochastic dynamic lot-sizing problem using bi-level programming base on artificial intelligence techniques

Cited by 16 publications

References 30 publications

Bilevel Multiobjective Programming Applied to Water Resources Allocation

Bilevel Multiobjective Programming Applied to Water Resources Allocation

A novel data-driven analytical framework on hierarchical water allocation integrated with blue and virtual water transfers

A linear bi-level multi-objective program for optimal allocation of water resources

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