Kazuyoshi Hidaka

Simulation-based approach to the warehouse location problem for a large-scale real instance

We simulated a large-scale Uncapacitated Warehouse (Facility) Location Problems (UFLP) in the real world on a digital map, and found an approximate solution. The problem was to find a near-optimal solution for the number and locations of warehouses that minimize the sum of the transportation cost and fixed cost, and meet the needs of 6,800 customers. The network data of the digital map were efficiently used to obtain candidate warehouse locations, to simulate the transportation cost, to simulate the warehouse fixed cost, and to find a near-optimal solution for the number and locations of warehouses. In this paper, we propose a simulation-based approach to the large-scale UFLP, including a new heuristic algorithm named “Balloon Search,” and give the results of our experiments.

An Approximation Algorithm for a Large-Scale Facility Location Problem

We developed a new practical optimization method that gives approximate solutions for large-scale real instances of the Uncapacitated Facility Location Problem. The optimization consists of two steps: application of the Greedy—Interchange heuristic using a small subset of warehouse candidates, and application of the newly developed heuristic named Balloon Search that takes account of all warehouse candidates, and runs in ( O (3n + 2n log n ) ) expected time (n is the number of nodes of the underlying graph). Our experiments on the spare parts logistics of a Japanese manufacturing company with 6000 customers and 380,000 warehouse candidates led us to conclude that the Greedy heuristic improved the total cost by 9%-11%, that the Interchange heuristic improved the total cost by an additional 0.5%—1.5%, and that Balloon Search improved it by a further 0.5%—1.5%.We developed a new practical optimization method that gives approximate solutions for large-scale real instances of the Uncapacitated Facility Location Problem. The optimization consists of two steps: application of the Greedy—Interchange heuristic using a small subset of warehouse candidates, and application of the newly developed heuristic named Balloon Search that takes account of all warehouse candidates, and runs in ( O (3n + 2n log n ) ) expected time (n is the number of nodes of the underlying graph). Our experiments on the spare parts logistics of a Japanese manufacturing company with 6000 customers and 380,000 warehouse candidates led us to conclude that the Greedy heuristic improved the total cost by 9%-11%, that the Interchange heuristic improved the total cost by an additional 0.5%—1.5%, and that Balloon Search improved it by a further 0.5%—1.5%.

The Clarion Call for modern services: China, Japan, Europe, and the U.S.

hat will modern services be like? Today many services are viewed as a craft activity—individual doctors, retail sellers, programmers all doing useful things their own way. There is, however, an increasing role for an organized, analytic, and engineering approach to all these activities. Evidence-based medicine, marketing sciencedriven retailers, and software engineering are examples of these trends. Automated services are a natural object of attention, since they can be observed in great detail, can be reconstructed and improved, and can be combined in new ways quickly and relatively easily. We are therefore seeing a rapid evolution toward an engineering approach to the life cycle of such services, and the application of mathematic and scientific approaches to the problems and opportunities they present. Complex service systems must be viewed at three levels: the functional attributes (what does it do and how does it do it?), nonfunctional attributes (management and control properties such as performance and security), and intentional attributes (what is the goal or purpose of the activity, such as societal benefit, private profit, or personal esteem?). Each level is susceptible to analysis, but different disciplines dominate. As computational services proliferate, new fields of study will open up, combining the computing, engineering, mathematical, management, and social sciences in creative ways. When we look at complex B2B projects, there is a growing application of solution engineering—using the best available techniques to the multiple phases of the activity, managing the risks, increasing predictability of quality and schedule, learning from experience in a project to improve not only the results of that effort but of succeeding solutions. As we examine the stages of a single large business service project (including requirements, design, implementation, deployment, and ongoing operation), and build up portfolios and service lines, much of the work can be formalized and subjected to analysis and radical improvement through optimization, evolutionary learning, and organization improvement. Of course, applying engineering thinking to such projects is not new—without such we would not have fields with names like “civil engineering” or large facilities like airports and suspension bridges. But the confluence of information-dominated services, techniques of computer science, and increasing experience is rapidly opening up new possibilities for modern service. A GLOBAL APPROACH Innovation is imperative to continued growth, increased productivity, and the general health of all economies. After a long history of contributions and breakthroughs to IT innovation, IBM Research is now directing resources toward innovation for the services industry: Business Design and Implementation. How does one model, design, and instantiate optimal business functions? What tools and techniques are needed to create abstractions of an enterprise, to effect the transformation from strategy down to underlying IT systems, and to monitor the end-to-end process? The Component Business Model (CBM) is one approach under development. What is needed to build and deliver industry solutions in an efficient, reusable fashion? Business Optimization and Management. How does one improve decision making and operations of ongoing business functions? How can business data be collected, analyzed, and exploited more optimally? How can business performance be enhanced as a result of the optimization of the underlying function, for example, supply chain? Given the importance of the work force in labor intensive services, how does one forecast, hire, allocate or shift resources to meet changing demand patterns? Services Delivery. In IBM’s internal service delivery centers, what are the best ways to maintain desired service levels while increasing efficiency and productivity? What tools and techniques can guarantee end-to-end manageability and visibility throughout the entire services life cycle from request to delivery? Challenges include the globalization of service delivery, adoption of standardized best practices, automation, virtualization of resources including labor, and the appropriate integration of the human element. Services Sciences Management and Engineering (SSME) applies to each of these areas [94]. IBM Research laboratories worldwide are engaging with local universities and governments on the topic of innovation in services, as described here.

Service Scienceservice science , Management, and Engineering SSME (SSME) in Japan

This paper reports the latest academic and government activities relating to Service Innovation and Service Science , Management, Engineering (SSME ) in Japan. Universities, government institutes, and government officials are looking for new ideas to cultivate economic growth, especially following the financial crisis that began in late 2008. Service innovation makes an excellent place to look for these new ideas, and SSME, as a new academic initiative for giving fundamentals for service innovation, may make an excellent basis for service innovation.

Practical Approach to a Facility Location Problem for Large-Scale Logistics

We developed a new practical optimization method that gives approximate solutions for large-scale real instances of the Uncapacitated Facility Location Problem. The optimization consists of two steps: application of the Greedy — Interchange heuristic using a small subset of warehouse candidates, and application of the newly developed heuristic named Balloon Search that takes account of all warehouse candidates. Our experiments on the spare parts logistics of a Japanese manufacturing company with 6,000 customers and 780,000 warehouse candidates led us to conclude that the Greedy heuristic improved the total cost by 9% – 11%, that the Interchange heuristic improved the total cost by an additional 0.5% – 1.5%, and that the Balloon Search improved it by a further 0.5% – 1.5%.

User-interface of a tool for learning geometry

Abstract This paper proposes new techniques for researchers and developers of drawing systems, especially software for learning and teaching geometry. The techniques allow them to draw geometric figures precisely by using geometric constraints, and to change constrained figures directly. Complicated figures can be easily manipulated by using an interactive, direct, and highly-graphical approach that is realized by a combination of control points and constraint buttons and by graphical tools such as a constrained marker, an electronic protractor, and an electronic divider. The techniques had been implemented as graphical user-interfaces of a micro-world for learning geometry (named GeoBlock). We observed how GeoBlock was used in classrooms and were convinced that students and teachers in junior and senior high schools could draw constrained figures easily by using it.

Development of GeoBlock: A Micro-World for Learning and Teaching Geometry

GeoBlock is a micro-world software tool for learning and teaching geometry, and has been prototyped on personal computers. It was designed according to the concept of direct manipulation of geometric figures under geometric constraints. A block is constructed to correspond to each complicated figure that is under geometric constraints, and it can be changed, re-used, and observed interactively on the computers display. From practical use in classrooms, we are convinced that GeoBlock is effective in two phases of geometry lessons. One is the phase of discovering rules among geometric webs that the students have not yet studied. The other is the phase of assimilating geometrical facts that they have already studied. GeoBlock shows one way in which a computer can help students to learn geometry, and can help teachers to give persuasive geometry lessons.