TY - JOUR
T1 - Convex optimisation model for ship speed profile
T2 - Optimisation under fixed schedule
AU - Huotari, Janne
AU - Manderbacka, Teemu
AU - Ritari, Antti
AU - Tammi, Kari
N1 - Funding Information:
Funding: This research was funded by the Aalto University School of Engineering doctoral school.
Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - We present a novel convex optimisation model for ship speed profile optimisation under varying environmental conditions, with a fixed schedule for the journey. To demonstrate the efficacy of the proposed method, a combined speed profile optimisation model was developed that employed an existing dynamic programming approach, along the novel convex optimisation model. The proposed model was tested with 5 different ships for 20 journeys from Houston, Texas to London Gateway, with differing environmental conditions, which were retrieved from actual weather forecasts. As a result, it was shown that the combined model with both dynamic programming and convex optimisation was approximately 22% more effective in developing a fuel saving speed profile compared to dynamic programming alone. Overall, average fuel savings for the studied voyages with speed profile optimisation was approximately 1.1% compared to operation with a fixed speed and 3.5% for voyages where significant variance in environmental conditions was present. Speed profile optimisation was found to be especially beneficial in cases where detrimental environmental conditions could be avoided with minor speed adjustments. Relaxation of the fixed schedule constraint likely leads to larger savings but makes comparison virtually impossible as a lower speed leads to lower propulsion energy needed.
AB - We present a novel convex optimisation model for ship speed profile optimisation under varying environmental conditions, with a fixed schedule for the journey. To demonstrate the efficacy of the proposed method, a combined speed profile optimisation model was developed that employed an existing dynamic programming approach, along the novel convex optimisation model. The proposed model was tested with 5 different ships for 20 journeys from Houston, Texas to London Gateway, with differing environmental conditions, which were retrieved from actual weather forecasts. As a result, it was shown that the combined model with both dynamic programming and convex optimisation was approximately 22% more effective in developing a fuel saving speed profile compared to dynamic programming alone. Overall, average fuel savings for the studied voyages with speed profile optimisation was approximately 1.1% compared to operation with a fixed speed and 3.5% for voyages where significant variance in environmental conditions was present. Speed profile optimisation was found to be especially beneficial in cases where detrimental environmental conditions could be avoided with minor speed adjustments. Relaxation of the fixed schedule constraint likely leads to larger savings but makes comparison virtually impossible as a lower speed leads to lower propulsion energy needed.
KW - Convex optimisation
KW - Dijkstra’s algorithm
KW - Speed optimisation
KW - Voyage optimisation
UR - http://www.scopus.com/inward/record.url?scp=85110297448&partnerID=8YFLogxK
U2 - 10.3390/jmse9070730
DO - 10.3390/jmse9070730
M3 - Article
AN - SCOPUS:85110297448
SN - 2077-1312
VL - 9
JO - Journal of Marine Science and Engineering
JF - Journal of Marine Science and Engineering
IS - 7
M1 - 730
ER -