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"It's not the stops you make, but the route you take that counts."

One of the classic, yet highly challenging, problems in the field of optimization is the "traveling salesperson problem" or TSP. This name was given to these particular types of problems because they involve variables akin to those a traveling salesperson might face - given a finite number of cities and the cost of traveling between them, find the cheapest way to visit all the cities and return to the starting point.

It's helpful to consider this class of problems when working with businesses that plan schedules and manage logistics, production scheduling or cutting raw materials. TSP expert, Hiroyuki Okano has been efficiently solving these types of problems for IBM clients for the past 10 years.

The challenge in TSPs is having to consider many 'stops' with multiple constraints. When solving a TSP, all possible combinations of stops are compared to one another to find the best solution. As the number of stops increases, the number of combinations increases exponentially, which makes the solution much more complex. The secret behind finding an effective solution in an efficient manner is to test as few combinations as possible to get an accurate result.

Hiroyuki enjoys working out efficient algorithms to solve TSPs. For a major steel manufacturer, he modeled a finishing line scheduling problem as a TSP and used a number of techniques to efficiently find a solution. He has also used these techniques to help increase production efficiency and reduce the time and effort required for production planning.

One of IBM's most valuable assets in its optimization practice is the Vehicle Routing Planner and Hiroki's contribution to this tool is important. Imagine the combinations that must be compared when figuring out the best routes for delivery trucks on a road network to minimize the number of trucks needed, but still meet the requirements for capacity, time and customer demand. Through the use of efficient algorithms, the Vehicle Routing Planner helps solve these types of problems. The algorithm Hiroyuki developed for the planner is designed to start by adding costs to the variables in the problem and then to find the best local solutions before testing to see if there are better combinations.

When not developing efficient algorithms to help solve TSPs, Hiroyuki is busy optimizing the routes he rides - on a horse. In his free time, he enjoys riding with the IBM Equestrian Club in Tokyo.