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Two-stage mean-risk stochastic optimization model for port cold storage capacity under pelagic fishery yield uncertainty

Zhimin Liu, Shaojian Qu, Mark Goh, Zhong Wu, Ripeng Huang and Gang Ma

Physica A: Statistical Mechanics and its Applications, 2020, vol. 541, issue C

Abstract: The problem of the optimal capacity of cold storage for pelagic fisheries under uncertain harvesting/production is studied. We establish a two-stage mean-risk stochastic optimization model, by considering the uncertainty of pelagic fishery yield and the risk measure of the cold storage cost loss. Applying a Benders-type scenario decomposition method, a modified cutting decomposition algorithm is proposed to solve the two-stage mean-risk stochastic optimization model, yielding the optimal capacity and maximal expected return of cold storage simultaneously. Further, the effects of the refrigeration cost, storage fee, weight of the conditional value-at-risk, and the confidence level on the expected profit are analyzed. We compare the modified cutting decomposition algorithm with a multi-cutting decomposition algorithm, to validate the proposed algorithm based on the computational time and the number of iterations.

Keywords: Two-stage mean-risk stochastic optimization; Conditional-value-at-risk; Port cold storage; Uncertainty; Decomposition algorithm (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:541:y:2020:i:c:s0378437119318680

DOI: 10.1016/j.physa.2019.123338

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