The Management Science Laboratory explores a broad range of topics in operations management, ranging from mathematical programming to numerical analysis. "We go wherever there is a mathematical problem." Our work begins when someone feels that a conventional operation is inefficient and could be improved. We strive to analyze the issue, discover underlying structures, and propose better solutions.
The scope of management science is remarkably diverse.
Scheduling: Is the production lead time too long? Are delays occurring frequently? We provide more efficient resource allocations and timetables.
Location Planning: Can we reduce the number of facilities while still providing adequate service to a region? We identify more effective facility deployment strategies.
Transportation Planning: How can we alleviate traffic congestion across a network? We conduct large-scale traffic flow simulations to evaluate potential scenarios.
Decision Making: How can we reconcile differing evaluations involving multiple alternatives? We construct pairwise comparison tables and other analytical tools to support consensus building.
We have long been engaged in these central themes of operations management. Our methodological approaches are equally diverse, including discrete algebra, control theory, graph theory, combinatorial optimization, and highperformance computing. For scheduling problems, we often apply control-theoretic or discrete algebraic frameworks. For location planning, sparse graph structures and mathematical programming frequently offer effective solutions. Because our research targets span a broad spectrum, maintaining a balanced and comprehensive perspective is essential.
If you already have a specific interest within management science, you have come to the right place; you can begin your research immediately. Even if you are still exploring and unsure of your direction, there is no need to worry. As long as you are comfortable with mathematics and programming, you will discover compelling research topics in our laboratory.
The chief research staff (Hiroyuki Goto), collaborative researchers, and several graduate students have engaged in the following themes:
1. Scheduling methods under limited resources
Keywords: max-plus algebra, optimal control, resource constraint, critical chain project management
2. Effective use of geographical information systems (GIS) data
Keywords: digital elevation, terrain analysis, data coding & encoding, parallel processing
3. Natural language processing (NIP)
Keywords: morphological analysis, indexing, classification & clustering, multivariate analysis
