Opt Eng Lab
　　


Welcome to Optimization Engineering Lab


    　Optimization Engineering Lab(OptEngLab) utilizes techniques such as management engineering, optimization, product design, process design, supply chain, scheduling, and agent systems to support evaluation, decision-making, and systematization for planning, management, and operations that consider safety, environment, quality, cost, and user requirements throughout the product lifecycle from production to disposal/recycling. The OptEngLab focuses on creating a system for the next generation of product development that encompasses both hardware-centered "monozukuri" and process-centered "kotozukuri" using systems engineering, computational science, and IT technology. The OptEngLab provides expertise on wise decision-making, and welcomes consultation with clients to collaboratively work towards a swift problem-solving process by combining both parties' knowledge.
    　If you are looking for a wise decision-making approach, please feel free to consult with us. Let's work together, combining our knowledge to swiftly solve problems.
    　　
  • Optimization Engineering challenges the horizon of infinite knowledge!
  • Optimization Engineering provides quick and flexible support for diverse problem-solving!
  • Optimization Engineering is a "practical science" rooted in the "magic science" of optimization! 　　
  • Optimization Engineering solves problems efficiently without waste, impossibility, or inconsistency! 　　
  • Optimization Engineering improves business and management without investment in equipment! 　　
  • Optimization Engineering enables continuous improvement in problem-solving capability!
　


What is "Optimization Engineering"?


    　This is a management system that aims to solve practical problems in technology and engineering, with optimization as the main element technology. The framework strives to rationalize the discovery, formulation, and application process of optimization problems for decision-making support.
    　　
  • Optimization theory: Theory and creation related to optimality. 　　
  • Optimization methods: Creating solutions by interpreting and applying theory and prediction. 　　
  • Optimization software and algorithms: Systems and environments where solutions are implemented.

    　These three elements are interconnected with Science for optimization theory, Engineering for optimization methods, and Operation for optimization software and algorithms.


What do our services include?


  • Developing problem-solving methods and systems for decision support based on computational science and technology
  • Providing advice, guidance, education, and awareness on the application and implementation of optimization technology
  • Providing advice, guidance, investigation, and awareness on production management
  • Planning and publishing books on the systematization and practical application of optimization engineering

    　We can support you in the following areas:

  • Developing problem-solving methods and systems for decision support in processes and systems based on computational science and technology
  • Optimization engineering
  • Smart decision making through intelligence
  • Environmentally benign technology
  • Multi-objective optimization
  • Uncertainty analysis and flexibility analysis

    For example, we can offer training and technical support on the above topics.
    Please feel free to contact us for more information.

      Training materials:

    • Fundamentals of optimization engineering: Aim of Optimization Engineering
    • Fundamentals of production system engineering: How to learn Production System Engineering
    • Fundamentals of optimization and decision support system: Introduction of optimization and decision support
    • Commercial books and other materials: Refer to Our Performances Section

      Computer usage technology (examples)

    • Development of software for analyzing the trade-off between economic efficiency and environmental impact in production and distribution systems
    • New software for analyzing the trade-off between economic efficiency and environmental impact
    • Development of a method for solving single-objective optimization problems using multi-objective evolutionary algorithms
    • Expanding the range of application of multi-objective evolutionary algorithms
    • Development of practical solutions for the VRP problem using 3D map data and traffic information
    • More reliable planning based on detailed information
    • Development of an elite-led evolutionary algorithm for post-analysis of multi-objective optimization
    • Supporting flexible and resilient decision-making.

      For examples, we have developed such as

        1. Multi-objective Optimization Algorithms
        　Balances and quickly optimizes goals to satisfy decision makers' preferences for wanting to do everything well.

      • RESTEM (Revised Step Method): Interactive method
      • MOON2/2R (Multi-Objective Optimizer cooperated with Neural Network/ of Radial basis) Refer to this
      • Post-analysis method for preferred optimal solutions
        　Creates multiple alternatives in the neighborhood of the preferred optimal solution to address various uncertainties (mathematical models, subjective evaluations, pending qualitative evaluation items, etc.)
      • Multi-objective analysis: Elite-induced evolutionary method
        　Controls Pareto front generation in accordance with decision makers' preferences
      • MOOMLE (Multi-Objective Optimizer cooperated with Machine Learning)
        　Enhanced version of MOON2/2R that streamlines the modeling capability of value functions with machine learning　

        2. Logistics Optimization Algorithms
        　Provides algorithms for optimizing diverse and large-scale logistics. Uncertain Logistic optimization

      • Hybrid Tabu Search (basic solution method)
        　Significantly improves logistics operating costs for major chemical companies with technical guidance　
      • Weber basis saving method
        　Evaluates transport costs based on Weber-type transport costs (dependent on both transport distance and weight)　 Weber basis Logistic optimization
      • Evaluates transport costs considering 3D map information (distinguishing between uphill, downhill, and flat terrain)
        　Cost evaluation that better reflects reality than others

        3.Meta-optimization Algorithms
        　Supports optimal decision-making through appropriate application of various meta-optimization algorithms.

      • Modified Tabu Search: Stochastically accepts worsening solutions
        　Enhanced performance with a hybrid solution with SA　
      • Binary PSO: 0-1 optimization problem
        　Demonstrated power through parallel computation in logistics optimization　
      • Adaptive DE: Incorporates generational features
        　Enhanced performance of original GA's real variable version.　
      • Non-linear simplex method for MOP
        　MOP version of non-linear simplex method incorporated with PSO　


    • Director Dr. Yoshiaki Shimizu's Profile and Qualifications


      Born in 1949
      Graduated from Osaka Prefectural Kitano High School in 1967
      Received a Bachelor of Science in Chemical Engineering from the Faculty of Engineering at Kyoto University in 1971, with a thesis titled "Ultra-Filtration Performance of Cellulose Acetate Membranes for Artificial Kidney."
      Completed the Master's Program in Chemical Engineering at the Graduate School of Engineering at Kyoto University in 1973, with a thesis titled "Setting and Control of Insensitive Systems in Chemical Reaction Processes."
      Completed the Doctoral Program in Chemical Engineering at the Graduate School of Engineering at Kyoto University in 1976, with a dissertation titled "Practical Design and Control in Chemical Reaction Processes on the Basis of Sub-Optimal Concept."
      Assistant Professor at the Research Reactor Institute at Kyoto University from 1976, promoted to Associate Professor in 1988.
      Professor at the Faculty of Engineering at Toyohashi University of Technology from 1997, retiring in 2014. Continued as Visiting Professor from 2014-2016.



    　During his time at Toyohashi University, he served as Assistant Dean of the Production Systems Engineering Department from 2001-2002, Department Chair from 2006-2010, and Course Leader of the System Control and Robotics Course in the Mechanical Engineering Department from 2010-2013.

    　Holds a Ph.D. in Engineering from Kyoto University,
    is certified as a Class 1 Radiation Worker (License No. 13538)
    and Emeritus Professor at Toyohashi University of Technology.

      Awards and honors include:

    • Science award of excellence for 2011 (ABI) (2011.6)
    • Top 100 Engineers (IBC) (209.10)
    • Marquis Who's Who in the World Inclusion (2009.6 - )
    • Academic Achievement Award from the Production Systems Division of the Japan Society of Mechanical Engineers (2019.3, with Jae-Kyeong Yang)
    • Academic Achievement Award from the Production Systems Division of the Japan Society of Mechanical Engineers (2015.3)
    • Academic Achievement Award from the Production Systems Division of the Japan Society of Mechanical Engineers (2013.3)
    • Excellent Presentation Paper Award from the Production Systems Division of the Japan Society of Mechanical Engineers (2012.3, with Tatsuhiko Sakaguchi)
    • Best Paper Award from the Society of Instrument and Control Engineers (2008.5)
    • Encouragement Award from the Society of Instrument and Control Engineers (2003.3, with Ken Wada)


      Was active in various social activities, such as serving as:

    • a member of a variety of academic societies such as Evolutionary Computation, Chemical Engineers, Mechnical Engineering etc
    • a member of the Process System Engineering 143 Committee of the Japan Society for the Promotion of Science
    • a recommendation committee member for the Japan International Award
    • a specialist committee member for the Science Research Grant Committee
    • an evaluation committee member for the Regional Development Project of the Ministry of Economy, Trade and Industry


    Our perfirmances


    　Here appears the lists of publications and research results related to multi-objective decision-making and optimization. The list includes original papers, technical papers, review papers, and conference proceedings, as well as information on grants received for research projects.



    　The most recent paper in the list is titled "Study on a Design Support Model in Closed-loop Manufacturing System Considering Multi-objective Optimization" and was published in the Journal of the Japan Industrial Management Association in 2022.
    　Other papers in the list cover topics such as multi-objective evolutionary algorithms, vehicle design optimization, and cost accounting for vehicle routing problems.
    　Some of the papers are available for download from J-Stage ( e.g., Chem. Eng., Mech. Eng., etc), & ResearchGate
    while others require a request for the full paper.



    Optimization Enginieering Lab

    [Zip: 594-0031] 4-10-90, Fuseya-cho, Izumi city, Osaka prefectire JAPAN
    Nearest staion：Komyoike of Senboku-Kosoku Line（15 min walk）