Robust price-setting newsvendor model with interval market size and consumer willingness-to-pay

Wang, Charles X.; Webster, Scott; Zhang, Sidong

doi:10.1016/j.ijpe.2014.04.006

Cited by 24 publications

(14 citation statements)

References 34 publications

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“…When the distribution of demand had known support, mean, and variance, Kamburowski [3] studied the single-period inventory management problem and derived the closed form formulas for the worst-case and best-case order quantities. Qin and Shang [4] and Wang et al [5] applied a robust optimization approach to stochastic inventory management problems. So far, the robust optimization approach [20] has become an important research direction.…”

Section: Incomplete Information About Probability Distribution Ofmentioning

confidence: 99%

“…In this case, decision makers do have not enough historical data to determine the exact probability distribution of demand. Under incomplete information about the probability distribution of demand, some interesting research studies have been documented in the literature [3][4][5]. Te stochastic approach seems to be less conservative than the worst-caseoriented robust optimization approach.…”

Section: Introductionmentioning

confidence: 99%

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A Distributionally Robust Fuzzy Optimization Method for Single-Period Inventory Management Problems

Guo

Sun

Tian

et al. 2023

Scientific Programming

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This paper investigates single-period inventory management problems with uncertain market demand, where the exact possibility distribution of demand is unavailable. In this condition, it is important to order a reliable quantity which can immunize against distribution uncertainty. To model this type of single-period inventory management problem, this paper characterizes the uncertain demand by generalized interval-valued possibility distributions. We present a novel concept about an uncertain distribution set to describe distribution perturbation characterization. First, we introduce a lambda selection of the interval-valued fuzzy variable, and the uncertain distribution set is a collection of all generalized possibility distributions of lambda selection variables. According to the uncertain distribution set, a new distributionally robust fuzzy optimization method is developed for single-period inventory management problems. Under mild assumptions, the robust counterpart of the proposed fuzzy single-period inventory management model is formulated, which is an optimization program with certain linear objectives and infinitely many integral constraints. We discuss the computational issue of integral constraints and reformulate equivalently the robust counterpart as three deterministic inventory submodels under generalized interval-valued trapezoidal possibility distributions. According to the characteristics of three submodels, a domain decomposition method is designed to find the robust optimal solution that can immunize against uncertainty in our single-period inventory management problem. Finally, some computational results demonstrate the efficiency of the proposed distributionally robust fuzzy optimization method.

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Section: Incomplete Information About Probability Distribution Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Distributionally Robust Fuzzy Optimization Method for Single-Period Inventory Management Problems

Guo

Sun

Tian

et al. 2023

Scientific Programming

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“…ere are thirty-five papers that had cited Wu and Ouyang [21] in their references. We list them in the following: Mostard et al [22], Wu et al [5], Ho [23], Annadurai and Uthayakumar [24], Tung et al [25], Çapar et al [26], Drezner et al [27], Lin et al [28], Wang [29], Zheng and Liu [30], Gholami-Qadikolaei et al [31], Ma and Qiu [32], Ouyang et al [33], Lin [34][35][36][37], Parvathi et al [37], Lin [38], Jindal and Solanki [39], Lin [40], Lin et al [41], Vishkaei et al [42], Wang et al [43], Madhusoodhanan et al [44,45], Chang et al [46], Jindal and Solanki [47], Madhusoodhanan et al [48], Chang et al [49], Sarkar and Mahapatra [50], Chuang et al [51], Hu et al [52], Maleki Vishkaei et al [53], Noh et al [54], and Singha et al [55]. Most of them only mentioned Wu and Ouyang [21] in their introduction but did not offer further study for Wu and Ouyang [21].…”

Section: Introductionmentioning

confidence: 99%

Novel Solution Method for Inventory Models with Stochastic Demand and Defective Units

Luo

Chu

Chao

2020

Mathematical Problems in Engineering

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This paper is a response to two papers. We improve the lengthy proof for the first paper by an elegant verification. For the second paper, we point out the three-sequence approach will result in different convergent rates such that when the other two sequences are converged, the ordering quantity sequence may still not converge to the optimal solution. We construct a novel iterative method to simplify the previous approach proposed by the three-sequence approach for the optimal solution. By the same numerical examples of three published papers, we demonstrate that we can control our findings to converge more accurately than previous results. Moreover, we show that there are three distinct features of our proposed approach. (i) It converges to the desired solution within the preassigned threshold value. (ii) We estimate the convergent ratio. (iii) We find the dominant factors for our proposed convergent sequence.

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“…For example, Kamburowski [6] provided new theoretical foundations for analyzing the case under incomplete information about probability distribution of random demand, Rossi et al [24] introduced a novel strategy to address the issue of demand estimation by combining confidence interval analysis and inventory optimization, Wu et al [31] studied a risk-averse situation with quantity competition and price competition based on conditional value-at-risk criterion and Sayın et al [25] considered both random demand and random supply and provided the optimal ordering policy and optimal portfolio at the same time. For the case with partial information, several authors such as Qiu and Shang [23], Turgay et al [27] and Wang et al [29] also apply robust optimization to handle the distribution uncertainty of probability parameters in the newsvendor or inventory problems.…”

Section: Introductionmentioning

confidence: 99%

A novel single-period inventory problem with uncertain random demand and its application

Wang

Qin

Kar

2015

Applied Mathematics and Computation

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Robust price-setting newsvendor model with interval market size and consumer willingness-to-pay

Cited by 24 publications

References 34 publications

A Distributionally Robust Fuzzy Optimization Method for Single-Period Inventory Management Problems

A Distributionally Robust Fuzzy Optimization Method for Single-Period Inventory Management Problems

Novel Solution Method for Inventory Models with Stochastic Demand and Defective Units

A novel single-period inventory problem with uncertain random demand and its application

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