Multi-Mile Logistics Optimization (Spreads)

About the Trainers LEARN PRACTISE Dr Le Van Dang is a Scientist at ARTC (A*STAR). He received his PhD in Computer Engineering & IMPLEMENT™ from Sirindhorn International Institute of Technology (SIIT), Thammasat University, Thailand. He specializes in the field of process optimisation for machining and system control, mathematical programming. His work and research interests are mainly focused on supply chain digital twin, AI industrial applications, optimisation algorithm development for production planning, scheduling, and transportation. Dr Irfan Soudagar is a Development Scientist at ARTC (A*STAR). He received his PhD in Operations Research from the National University of Singapore. He specializes in the field of Robust Optimisation techniques dealing with optimisation problems under future uncertainty. He also has research experience in the topics of Optimisation, Machine Learning, Logistics & Supply Chain Management. He holds a dual degree, Bachelor’s in Manufacturing Science and Master’s in Industrial Engineering from the Indian Institute of Technology Kharagpur. Mr Chew Kim Hoe is a Development Engineer at ARTC (A*STAR). He completed his Master’s in Aerospace Engineering specializing in Systems Simulation from the Nanyang Technological University. His experiences in the supply chain field includes digital twin modelling, network optimisation/simulation and disruption management Ms Adlakha Aarzoo is a Development Engineer at ARTC (A*STAR). She completed her MSc in Systems and Project Management from Nanyang Technological University. She holds a Bachelor’s degree in Engineering from the National Institute of Technology Kurukshetra, and has industry working experience of over 5 years. \\ When and Where Dates: 30 May to 2 June 2022 MULTI-MILE LOGISTICS Time: 9.00am to 6.00pm OPTIMISATION Venue: Advanced Remanufacturing and Technology Centre (ARTC) 30 May to 2 June 2022 3 CleanTech Loop, #01/01, CleanTech Two, Singapore 637143 Registration Please register online at www.a-star.edu.sg/ARTC/KTO Contact Us For general enquiries, please contact: Dr Edwin Soh, Senior Business Development Manager at [email protected] For technical information, please contact: Dr Le Van Dang, Scientist at [email protected] Scan the QR code for more information. Organised by: Funded by: 04/22

Course Outline Skills Course Reference Number: TGS-2022010986 (32 training hours) The programme employs the Learn-Practise-Implement™ (LPI™) pedagogy, focusing on optimisation problems in multi-mile logistics, where the tools and techniques taught will be reinforced with hands-on practices. With the emerging technologies and data integration, supply chain logistics strategies are more collaborated Fundamentals of multi-mile LEARN- Optimisation opportunities than before. This allows for integrated logistics planning which adds-up values to the overall supply chain. logistics PRACTISE- in multi-mile logistics and Instead of local planning and operating as in single-mile logistics (first, middle, last-mile), the modern IMPLEMENT™ approach of multi-mile logistics provides a centralized system for effective planning and control. Identifying and modelling their business impact optimisation problems (LPI™) In this course, a comprehensive set of terminologies and technical approaches will be covered to provide Tools and techniques for trainees with necessary skills to design, plan, and evaluate typical multi-mile logistics problems applicable Relevant industry use case optimising multi-mile in relevant industrial use cases. discussions logistics problems About this Programme Hands-on solution implementation for use cases In this programme, the participants will gain firsthand understanding of multi-mile logistics concepts, tools, and techniques to identify and solve optimisation problems towards designing efficient logistics networks. Upon Completion of the Programme This programme consists of four full-day sessions covering key concepts of multi-mile logistics, methods for Participants will be awarded with a certificate of identifying optimisation opportunities in logistics networks, problem modelling and hands-on implementation attendance by ARTC. of solution tools and techniques motivated using practical industry related case studies. The following tools would be used during the course: Course Fee and Funding • Python (Programming tool) • The nett course fee for all Singaporeans, SPRs and Long Term Visit Pass Plus Holders is S$780 (before • Excel, KNIME (Data tools) GST). • CPLEX, Gurobi (Optimization solvers) • anyLogistix (Logistics analytics/simulation software) • Singaporeans, SPRs and Long Term Visit Pass Plus Holders who are employed and fully sponsored by SMEs can claim an additional 20% of the full course fee with the Enhanced Training Support for SMEs After successfully completing the course, participants will have a clear understanding on the business impact Funding scheme (ETSS), subject to approval by SSG. of multi-mile logistics optimisation and gain necessary skills to work on industrial problems aimed at logistics network optimisation. • Singaporeans aged 40 years and above can claim an additional 20% of the full course fee with the Mid-Career Enhanced Subsidy (MCES). Who Should Attend • Singaporeans aged 25 years old and above are eligible for SkillsFuture Credit which can be used to This programme is relevant for business owners, management, executives, engineers, and professionals who offset course fees (for self-sponsored registrations only). are currently employed or who wish to be employed in supply chain and/or logistics related fields. It is applicable for organisations with the intentions to: • The full course fee before funding is S$2,600 (before GST). • Have a firsthand understanding of or to develop capability of multi-mile logistics optimisation. For more information about the funding, please visit SkillsFuture Singapore website at www.ssg.gov.sg • Understand the challenges and optimisation opportunities in their current logistics network for better delivery service at lower logistics costs. • Hands-on implementation of tools and techniques to re-design and optimise their current logistics network. Moreover, it is applicable to individuals and staff who are seeking a firsthand understanding of the concepts and optimisation techniques in multi-mile logistics, and capability improvement in terms of problem modelling and solving towards logistics optimisation.