TY - JOUR
T1 - Including robustness considerations in the search phase of Many-Objective Robust Decision Making
AU - Eker, Sibel
AU - Kwakkel, Jan H.
PY - 2018
Y1 - 2018
N2 - Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery phase to identify the vulnerabilities. In its original inception, the search phase identifies optimal strategies for a single reference scenario for deep uncertainties, which may result in missing locally near-optimal, but globally more robust strategies. Recent work has addressed this issue by generating candidate strategies for multiple policy-relevant scenarios. In this paper, we incorporate a systematic scenario selection procedure in the search phase to consider both policy relevance and scenario diversity. The results demonstrate an increased tradeoff variety besides higher robustness, compared to the solutions found for a reference scenario. Future research can routinize multi-scenario search in MORDM with the aid of software packages.
AB - Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. MORDM has four phases: a systems analytical problem formulation, a search phase to generate candidate solutions, a trade-off analysis where different strategies are compared across many objectives, and a scenario discovery phase to identify the vulnerabilities. In its original inception, the search phase identifies optimal strategies for a single reference scenario for deep uncertainties, which may result in missing locally near-optimal, but globally more robust strategies. Recent work has addressed this issue by generating candidate strategies for multiple policy-relevant scenarios. In this paper, we incorporate a systematic scenario selection procedure in the search phase to consider both policy relevance and scenario diversity. The results demonstrate an increased tradeoff variety besides higher robustness, compared to the solutions found for a reference scenario. Future research can routinize multi-scenario search in MORDM with the aid of software packages.
KW - Multi-objective optimization
KW - Robust decision making
KW - Scenario diversity
KW - Scenario selection
UR - http://resolver.tudelft.nl/uuid:10b6ab1b-b4da-4c4c-b003-b5d57c1ab22a
UR - http://www.scopus.com/inward/record.url?scp=85045697683&partnerID=8YFLogxK
U2 - 10.1016/j.envsoft.2018.03.029
DO - 10.1016/j.envsoft.2018.03.029
M3 - Article
AN - SCOPUS:85045697683
SN - 1364-8152
VL - 105
SP - 201
EP - 216
JO - Environmental Modelling and Software
JF - Environmental Modelling and Software
ER -