Port Multimodal Inland Mode of Transportation Predictor & Prescriptor

Home , Borgerhout, Ekeren, Port of Antwerp, Wilrijk

Minisymposium: Mathematics of Logistics: emerging trends in Optimization and Simulation modelling

Port Multimodal Inland mode of transportation predictor & prescriptor

Stefano Persi1*, Carlos Morillo2 1. Mosaic Factor, Spain, [email protected] 2. Mosaic Factor, Spain, [email protected]

Abstract The steady increase referred to the goods moved by containers in the different ports of Europe, as well as all around the world, the volume of TEU’s has augmented 20% in the last 10 years, has implied an increase of the inland transportation that has posed economic, social and environmental challenges to ports, and their hinterland. To tackle this issue, one of the innovative tools that the European Commission’s project, COREALIS, is developing, is the Cargo Flow Optimizer (CFO) tool, that uses the data available from the key port stakeholders (Port Authority, Terminal Operators, inland transportation operators, etc.) to create a predictive and prescriptive model in order to improve multimodality. The proposed tool, aims to improve the port operations while at the same time it reduces the current negative impacts in the surrounding area.

Keywords: MULTIMODALITY, LOGISTICS, PREDICTION

1. Introduction Ports are essential for the European economy; 74% of goods exported or imported to the EU are transported via its seaports. At the same time, the challenges they face are only getting greater: Volumes of cargo increase while they also arrive in a shrinking number of vessels: Post-Panamax vessels have a capacity of more than 18.000 containers. Port operators need to comply with increasingly stricter environmental regulations and societal views for sustainability. A sustainable land-use strategy in and around the port and a strategic transition to new, service-based, management models that improve capacity and efficiency are paramount. They are key enablers for ports that want to keep pace with the ocean carriers needs and establish themselves as trans-shipment hubs with a ‘societal license to operate’; for ports whose land strategy, hinterland accessibility and operations are underpinned by circular economy principles. In this sense, the European Union (EU) is putting significant effort in order to improve and optimize the efficiency of the European ports. To achieve this goal, a number of European projects have been funded within the Ports of the Future program, with COREALIS being one of them. COREALIS proposes a strategic, innovative framework, focused on disruptive technologies, including IoT, data analytics, next generation traffic management and 5G, for modern ports to handle future Port Multimodal Inland mode of transportation predictor & prescriptor capacity, traffic, efficiency and environmental challenges. Through COREALIS, the port will minimize its environmental footprint to the city as well as decrease disturbance to local population through a reduction in the congestion around the port. To tackle these challenges, one of the innovative tools that the COREALIS project will develop is the cargo flow optimizer (CFO) tool that develop a model based on data available from the key Port stakeholders (Port Authority, Terminal Operators, Inland Transportation Operators, etc.) that allows to predict and prescript different solutions related to the port operations as well as to the multimodal transport.

2. Main issues related to port multimodality operations It is already known that one of the basic problems related to the ports and their inland connectivity is referred to the trucks, as the most common inland mode of transport, and the different issues that arise with that mode all along the port and its surroundings. Nowadays, the most commonly used mode of transportation is road transportation. Several reasons make this mode the best fitted for all the carriers: • Road transportation allows a much wider schedule flexibility due to its main dependence to the driver and its almost full independence to any other issue (shared transportation, rigid timetables, etc.) • Road transportation allows to move the cargo independently of the number of containers required by the shipper • Finally, road transportation does not depend on any prioritizing rule that any other transportation mode can apply – the most common case is the one related to rail transportation where passengers are normally prioritized in front of goods Although for carriers road transportation is often the best solution, this option has different problems that make this solution one to be, at least, mitigated and adjusted to the real needs of all the stakeholders: • The port detects that a high number of heavy vehicles in the roads of the installation, implies a reduction of the productivity and an increase of congestion and the appearance of a bottleneck • The terminal and specifically its internal operations, due to the bottleneck that arises with the congestion, can be affected implying a relocation in-real-time of the containers and a reduction of the productivity • Finally, in the surroundings of the ports different issues related to road inland transportation appear: traffic congestion, atmospheric and acoustic contamination, increase of accident rate, visual impact, etc. These side effects are increased due to, normally, next to the port is located an urban area and, implying that the negative effect of the different impacts affect economically, socially and environmentally to the mentioned urban area. In fact, one of the key reasons not to use other inland transportation modes is related to the lack of information of these alternatives as well as the option to access, as customers, to these options independently of the total volume to be transported.

Port Multimodal Inland mode of transportation predictor & prescriptor

3. Scope of study To analyze the issue, we decided to work with the Port of Antwerp. This port is located next to the most populated city of Belgium (and the 2nd metropolitan area behind Brussels) and was in 2017 the 2nd container port of Europe behind Rotterdam (and the number 17 in all the world in 2014) with almost 9 Million TEU per year.

A4 (NL) (via Bergen op Zoom) Antwerp - Rhine Port Schelde - Rijnkanaal COMBINANT Amsterdam NORTH SEA ZANDVLIET Noordlandbrug 11 N E T H E R L A N D S Rotterdam ± INE RH Nijmegen Moerdijk Gorinchem BASF 755B757 Groot Buitenschoor ZANDVLIET 753A 759 Antwerpen Duisburg INEOS 729 Zeebrugge STYROLUTION 751A 761 727 Insteekdok 4 763 Venlo Neuss 723 719 K a 765 Gent AIR LIQUIDE EUROCHEM n T 715 LD Köln INDUSTRIES BELGIUM a 767 E CH R a S 713 Halluin H G E R M A N Y l I d BRUSSELS N 769 E S915 711 o Liège B E L G I U M k 12 S913 PSA ANTWERP 771 S911 709 S909 NOORDZEE TERMINAL B PUTTE S907 707 3 BERENDRECHT S905 775 Valenciennes Frankfurt S903 S901 705

Frederik-Hendrikbrug 703 Mainz 701 ZANDVLIET De Zouten Oudendijkbrug SLUIS Zandvlietbrug S869 BEREN DRECHTSLUIS LUX. S867 Berendrechtbrug Ludwigshafen S865 669 BERENDRECHT PSA ANTWERP 667 S863 EUROPA TERMINAL Germersheim Prosperpolder Noord S861 665 Insteekdok 3 Reigersbos S859 F R A N C E 661 Schor Ouden Doel K S857 Opstalvalleigebied PARIS 663 a S855 n Stuttgart Doelpolder Noord Paardenschor a S853 GUNVOR a Strasbourg PETROLEUM ANTWERPEN l d o HANDICO SEA-TANK E k 772 TERMINALS STABROEK N D TERMINAL I

SOLVAY B 770 H MEXICONATIE R Brakke Kreek 2 736734 740738 N INEOS OLEFINS & 768 A.B.T. 744742 732 649 748746 POLYMERS EUROPE 766 752750 730 PROSPERPOLDER 756754 STABROEK Ottmarsheim 647 764 760 758 dok 728 ELECTRABEL Insteekdok 2 762 aide 722724726 13 A elw 718720 645 D 714 716 Weil am Rhein 1800 643 710712 Basel INOVYN MANUFACTURING 706708 ANTWERP CONTAINER L BELGIUM 702 704 TERMINAL kerncentrale Doel VESTA 700 SEA TANK R TERMINAL 624 TERMINAL, K700B SOLVAY 622 KAPELLEN E 629B 620 618 MONSANTO 625C 627B EUROPE Insteekdok 1 616 D 625B 621A 614 Meeuwenbroedplaats 2 SYNEGIS 617 Berendrecht R EASTMAN 623 610 INDAVER E 615 608 606 650 OILTANKING 613 604 STOLTHAVEN 13 HOEVENEN N DOEL 611 l ne Galgeschoor tun EVONIK ns KANAALDOK B1/B2 a 540 m rug 536 1746 ijs ob LILLO T Lill 534 D 550 AMORAS A S u 532 12 541 c w Fort Lillo h v Blauwhoef u a 530 1744 il a 560 g d 528 SLIH o r n LILLO t MIDA-zone SLIL i k 1742 d 12 l 526 EUROPORTS SLIH in 533 b e CONTAINERS, K524 r n 524 1740 e n Kuifeend 1743 v 522 MAIN HUB 1700 SPCN r u o t (IFB) 1702 1900 k COVESTRO 531 520 EUROPORTS TERMINALS 1738 o BRASSCHAAT SPCZ p e ANTWERP DIV. MANUFERT s o 529 k 518 gedempt Doeldok h FRX K k 1704 e s 1736 o POLYMERS o n 527 a 1974 h 516 Vormingsstation Antwerpen-Noord d s e LBC n k 514C MSC PSA k 1706 ASHLAND Fort Liefkenshoek n f CEPSA a 1734 c e 525 Grote Kreek INEOS k e a 514B EUROPEAN TERMINAL n 1920 f i PHENOL L ld 500bis 1650 (MPET), K1742 a 1910 ie Schelde 521 512F g 1708 ADPO L o Oorderen KIELDRECHT 1648 1732 r 1930 MONUMENT 510C SEA-TANK Putten Weide 1654 LLH k 1646 u 1710 CHEMICAL TERMINAL, K510 ANTWERP STONE 1652 517 B 1644 e 512C TERMINAL (AST) 1730 D 1 508 Putten West ANTWERP GATEWAY 515 CARGILL 1658 k 1642 1950 506 Zoetwaterkreek o 1712 TERMINAL 1940 1933 513 ITC RUBIS ld 1728 1949 1968 COIL 1660 1640 1934 511 TERMINAL TERMINAL ANTWERP e INDAVER 1948 504 1664 o LANXESS 1638 1714 SLECO 509 HUPAC INTERMODAL Ekerse Putten LEUGENBERG Kleine Weel D 1726 INDAVER 502 15 1359 1636 507 PSA BREAKBULK ZUIDNATIE BREAKBULK Grote Geule 1724 IBOGEM Ketenisseschor 500 13551668 1716 MSC PSA 505 1634 FERTIKAL 1992 498 496 494492 490488486 484 482480478 476 474 472470468 466 1353 1720EUROPEAN TERMINAL 464 ANTWERP 1938 503 EKEREN 1351 Ketenisbrug (MPET), K1742 Churchilldok Grote Weel 1632 COLD STORES ORGACOM VOPAK TERMINAL 430 1349 428 1742bis GRENS INSPECTIE 1996 ACS 501 402 404 406 408 410 412 414 416 418 420 422424 426 Bospolder 1630MEDREPAIR S11 1793 Meestoofbrug POST (GIP) LUBRIZOL 400 1345 1628 KIELDRECHTSLUIS 1999 BOUDEWIJNSLUIS PSA ANTWERP NOVA NATIE Ekers Moeras GLOBAL CONTAINER INDUSS I CHURCHILL TERMINAL 1626 Prosperbrug 1610 352 ATO 1343 1622 1612 SERVICES 1993 Van Cauwelaertbrug Boudewijnbrug 1608 11 LANXESS 350 1341 1301 1620A 1992 VAN CAUWELAERTSLUIS SHIPIT 1606 SAINT-GOBAIN 348 Wilmarsdonk 1303 1253 1618 CONSTRUCTION PRODUCTS AET 1339 k 1614 Noordelijk 1604 Kruisschansbrug 300 6 WAASLANDHAVEN 256 306B e 346 EKEREN o 1251 W insteekdok 1602 344 1337 1305 a 1616 304 H d 1249 a 1602 NOORD 252 a 342 KLEINE BAREEL E

s BOREALIS SALLAUM E k l 1548 SBA 493 306 v 340 E a 3 1307 1247 1568 250 200bis 3 e n KALLO SEA-TANK e TERMINAL 1 1335 308 16 4 1245 491 n 1

SRP ( d 1600 338 9

o k 487 TERMINAL, K300 D Drijdijck 248 3 d (

a GRC KALLO Loghidden city 310 ( N r 1309 1243 5 (

485 o ) N n Luithagen v 336 H 1333 1504 312 a 483 246 k L b ICO R i

1562 L a a a 314 334 ) e 1241 l LAWTER u ) 1311 s 244 E

r 1560 479 423A h

SAGREX 477 s R 1331 r 316 332 B l i r e 1558 242 n o 1201 1520 KATOEN NATIE CNH r e 1313 KALLO 318 330 g l

e e 1239 1199 473F475 423C 421 328 d t t k H TRACTOR e t

VOPAK TERMINAL 1556 TOTAL 240 320 322 324 d 1329 V n BNFW 326 h e / 1203 B.S.T. 1512 9 b

1328 o 419 a 1 a 425 o E L 1315 1554 n r LEFTBANK RAFFINADERIJ 473D A.B.T. i

1197 238 ) e Melselebrug d

n v 1237 d u 473C 417 i è 427 t t a e Marshall- s 236 CNHI e g m n 473A 415 a n

KALLOSLUIS e nEUROFRUITPORTS e dok 433B d BELGIUM 1235 Zuidelijk 447bis 413 234 / e 1193 r 1103 1100 Farnesebrug o BNFW LUMIPAPER 111111091107 e 471 411 BNFW 192 s insteekdok 455 437 SEA-TANK k 232 196194 1233 a 1209 v 453 409 230 226 224222220 218216 214 212 210 190 BNFW 1183 1127 1113 e 457 TERMINAL 228 208 206 202 Verrebroekse Plassen KATOEN NATIE r 469 443 407 Wilmarsdonkbrug Oosterweelbrug 188 V 1181 1119 B 459 451 203 TERMINALS 1231 1211 1125 Leopolddok 135 131 129 186 184 182 180 178176174172 1175 1140 449 405 207 1121 Melkader Fort Sint-Filips 467 461 229 227 225 223 221 219 217 213 211209 170 1123 VOLLERS 127 3e Havendok 1998 1229 1213 465463 DDM5 231 NOORD NATIE A.B.T. 158160 162 164 OILTANKING ANTWERP ADPO EXXONMOBIL BELGIUM C.STEINWEG 166 168 1071 TOTAL OLEFINS 403B 237 235 TERMINALS VANHEEDE 156 EUROPORTS TERMINALS 1215 GAS TERMINAL BELGIUM A 1227 ANTWERP 239 ENVIRONMENTAL LOGISTICS 154 ANTWERP DDM2 121 lb VERREBROEK EUROPORTS TERMINALS ENGINE M10 241 243 245247 249 251253 255 257 152 150148 146142 1225 1143 Steenlandpolder 261 MAC² SOLUTIONS e LEFTBANK 1145 DOCK REPAIR M6 119 r 140 1069 M9 4e Havendok t 2e Havendok 1223 267A W.W.R.S. d 130 132 134 136 138 MERKSEM 12211219 KALLO M2M11 285 283 281 269 117 1147 Fort Sint-Marie 279 277 275 273271 o 128 HOLCIM CEMENT 1067 M3 SCR ATPC LBC 73 115 k ANTWERPEN VOTORANTIM DDM6401 126 1261 Land Van Waas 10 SIBELCO 113 TERMINAL DREDGING INT. 385 VOPAK TERMINAL N 81 124 WERF & VLAS NATIE In oo WIJNGAARD NATIE 1167 1165 1025 d EUROTANK ATPC rd 122 ZUIDNATIE 1218 1099 u 399 301 NOVAEDES ka TERMINALS 1268 HAZOP WAASLANDHAVEN st st 1269 ri 303 305 307 309 311 313 315 317 319 321 do ee 120 Spaans fort 1267 TOTAL OLEFINS ed 397 75 k l- 107 DISTRI ZUID 1166 ZUID EXXONMOBIL o 395 118 ANTWERP k Oos8t1erweel 105 5e Havendok Noordkasteel- 104ANTRECO 2 Rietveld Kallo Vlakte van Zwijndrecht 1023 373371369 367 363361 359 357 355 353 351 349347 bruggen Haasop R 91 A.B.T. 103 102 5DE 55 93 Groot Rietveld SIZ KATOEN NATIE TERMINALS A 95 97 100 HAVENDOK 54B me 101 TOTAL RAFFINADERIJ BECO2 SIO rik 99 SPECIALTY POLYMERS 5DE ad ANTWERPEN ARKEMADOW 1013 TOTAL OLEFINS TOTAL POLYMERS ok Straatsburgbrug ANTWERP 343 HAVENDOK S 1099 1075 ANTWERP ANTWERP 48 traa NIPPON MOMENTIVE 49 47 62 61 ts- MERKSEM 1089 Put van Fien BOREALIS Noordkasteel burg 1087 SHOKUBAI ESSENT BYK dok 1 1009 roeivijver e E 34 INEOS OXIDE SIKA SAOW DD 9 44 k BILFINGER ROB 1007 SPO STRAATSBURGDOK k MAINTENANCE PRAXAIR DD 8 43A

o DEMAKO ROYERSSLUIS 9 PARTNERS k 28C n 1053 ARLANXEO BELGIUM MELSELE MENNENS DD 5 o al

d 28A K KURARAY EXXONMOBIL 27B a

n k / BELGIUM a j Houtdok

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d e ENGIE FABRICOM o

t 39 lb n d A

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KATTENDIJKDOKSLUIS a z

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Z BELGIUM S29 L 1005 16A K Blokkersdijk dok 29C o 9 3M 22B b

4 36 34 r DEURNE Sint-Annabos S28 29E o

N e WAASLANDHAVEN 1423 k 8 d OOST S27 24 o S26 k 12A9 3 4B 5A 8 DEURNE 12 10 7 6 2 Waaslandtunnel 7 SINT-ANNA LINKEROEVER S24 MELSELE Vlietbos S23 Het Rot S22 SPVD VRASENE Voe tgan S21 ger stun LINKEROEVER nel 6 S19A Centraal S18A Á' S17B Station

BEVEREN E

ANTWERPEN E

S17A E 3

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4 1

ZWIJNDRECHT 3 4

Galgenweel (

S16 D 4 3

Distributiezone / Distribution area ( ( N

) D H

L BORGERHOUT R )

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Watergebonden goederenbehandeling / Quayside cargo handling s

ZWIJNDRECHT E h s a i r e c 17 S14 n g l h

K d t e

Bestaande industrie / Existing industry e S13B h

e / Burchtse Weel b n

o n L i , e v i n è K S12 t Beschikbaar haventerrein / Available port site e e g ö S11 n

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n y / Bestaande waterweg / Existing waterway tu n S9B HET ZUID BORGERHOUT KRUIBEKE n Woonkern / Residential area 16 BURCHT S8 e 3 S7 l S6 5a Groene ruimte / Green area S4S5 S3 S2 wvb - wegverbinding SPPN S1 IKO 1 SPPZ R spoor SCAS KUWAIT ALCA BERCHEM PETROLEUM Werken in uitvoering / Work in progress BP/BLP Blue Gate Antwerp

0 500 1.000 2.000 KIEL 7 Hobokense polder m 1 BERCHEM E 4 5 r Luchthaven Bron: havenGIS Deurne WILRIJK

Uitgave: September 2018 E

Figure 1: Port of Antwerp

The selection of the port of Antwerp (PoA) was motivated for many reasons:

• PoA is one the biggest ports in Europe and it is strategically located about 88 kilometers from the North Sea at the upper end of the tidal estuary of the river Scheldt

• The city of Antwerp, with more than half a million inhabitants is next to the port

• The roads that are going from and to the port are saturated with trucks involving Antwerp as the most traffic saturated urban area in Belgium and one of the most congested in all Europe

• The location of the Port allows not only to use rail and road mode but also barges to transport the goods inland

Port Multimodal Inland mode of transportation predictor & prescriptor

Figure 2: Antwerp inland connectivity

4. Methodology In order to improve the different issues that arise related to the port, the terminal and the urban area, our main goal has been to define a solution that allows to obtain an improved multimodal split of the containers that arrive at the terminal and are needed to be sent to final destination. The idea is to promote data sharing between the different key stakeholders in order to obtain the data required to create a tool to be able to develop a predictive and prescriptive model based on real and historical data, that allows the different stakeholders to choose the best option to optimize the supply chain. To achieve the goal, we are developing the CFO, a tool that allows to improve the internal organization of the terminals as well as gives to the carrier different alternatives in order to decide the best choice related to inland mode of transportation. The CFO in focused on the following goals:

a) To improve organization of containers placed on port’s terminal Development a prediction model based on real data (both historical and real time) provided by the different key stakeholders in order to obtain in advance the terminal occupancy as well as the inland mode of transportation expected to be used.

Port Multimodal Inland mode of transportation predictor & prescriptor

Improve organization

Datasets

• Port Authority Output • Terminal operator Data sharing • Terminal occupancy • Inland transport operators Predictive model Historical • Inland mode of transport expected st Real Time Data Big Data a) Creation of a 1 Big&Small b) Optimization of Lake output based on Data the 1st output historical data incorporating real time data

Figure 3: Improve organization of containers model

To improve the organization of containers, data sharing will be the base to create a two-phases predictive model where first a prediction based on historical data is made and – in real-time and constantly updated – a second prediction optimizes the final output adjusting the initial results obtained.

b) To predict the best available inland transportation to achieve final destination Analyse the inland requirements of the container as well as the inland transportation connections in order to predict the best existing available mode of transport

Inland transportation mode - Availability

Datasets

• Terminal occupancy • Inland mode of transport expected Output Output Output Data collection Predictive model • Prediction availability of inland • Inland transport connections Real Time transport routes based on transport • Modelling Simulation Recommendation time and cost of the route Inland Inland Capacity of transport connections Predictive Machine Learning

Figure 4: Inland transportation mode-Availability model

To predict the availability of inland transportation mode, a two-step scheme is created. First of all, a modelling of the different options is created. Following, a simulation based on the demand expected allows to recommend the best option based on the availability of the different existing modes of transport.

c) To propose new shared services related to inland transportation Analyse the different destinations related to containers in order to propose the creation of on-demand inland routes in order to optimize this inland transportation

Port Multimodal Inland mode of transportation predictor & prescriptor

Inland transportation mode – Proposal of new shared services

Datasets

• Terminal occupancy

Output • Inland mode of transport expected Data collection Output Prescriptive model • New shared transportation services • Inland transport connections Real Time proposal Modelling Simulation Prescription of new Inland • Capacity of transport connections Predictive shared services • Prediction availability of inland Machine transport routes based on transport Learning

Output 2 time and cost of the route

Figure 5: Inland transportation mode-New Shared services model

To prescript new shared services, a two-step scheme similar to the previous goal described is developed. First, a modelling of the different options is created. Following, a simulation based on the demand expected allows to propose new shared services combining different modes of transport.

5. Next steps and conclusions

The project began in May 2018 and it is expected to be finalized in April 2021.

Figure 6: Cargo Flow Optimizer Plan

Currently, the different scenarios as well as the data required to develop the CFO have been defined and we are just receiving the data in order to develop a first version of the CFO to be submitted in August 2019.

Acknowledgement This work is a part of the COREALIS project. COREALIS has received funding from the European Union’s Horizon 2020 research & innovation programme under grant agreement no 768994. Content reflects only the authors’ view and European Commission is not responsible for any use that may be made of the information it contains.

Port Multimodal Inland mode of transportation predictor & prescriptor

References

1. Notteboom, T. (2018). PortGraphic: the top 15 container ports in Europe in 2017. Retrieved January 3, 2019 from https://www.porteconomics.eu/2018/02/28/portgraphic-the-top-15- container-ports-in-europe-in-2017/

2. Corealis website, https://www.corealis.eu

3. https://www.porttechnology.org/news/the_worlds_top_30_container_ports