Mathematical optimization software development services
What is mathematical optimization software development service?
Mathematical optimization is a technique for finding the optimal solution to a problem with various constraints.
For this service, we will select and implement the most appropriate mathematical optimization algorithm for your requirements and target problem, and develop software to perform the mathematical optimization.
We can also implement customer-specified algorithms, as well as accelerate, improve the performance of, or refactor your mathematical optimization software.
- Implementation of mathematical optimization algorithms
- Acceleration, performance improvement, and refactoring of mathematical optimization software
- Survey of the latest mathematical optimization algorithms
- Consulting on the introduction of mathmatical optimization and mathematical optimization using quantum computation techniques
Examples of mathematical optimization algorithms
The following are examples of algorithms that we can support. Algorithms not listed here are also available.
- Local search
- Simulated annealing
- Tabu search
- GRASP
- Genetic algorithm
- Quantum annealing
- Branch and bound
- Quasi-Newton method
- Conjugate gradient method
- Trust region method
- Primal-dual interior point method
- Sequential quadratic programming
- Nelder-Mead method
- CMA-ES
- Differential evolution
- Particle swarm optimization
Examples of business results
- Development of optimization numerical control software for semiconductor manufacturing equipment
- Development of 2-D region optimal segmentation software
- Development of data assimilation system for seismic waves
- Mathematical optimization of redundant manipulator inverse kinematics
- Development of experimental condition optimization program by Bayesian optimization
- Development of solver for vehicle routing problem
Examples of mathematical optimization applications
- [Facility location optimization]
- In facility location optimization, we seek from among the potential sites for construction of facilities a construction location that minimizes various costs, such as construction costs, while satisfying the demand of customers in the area. For example, it can be used when considering the construction, decommissioning, or integration of various facilities and equipment, such as factories and production lines within factories, warehouses, hospitals, stores, and disaster evacuation facilities.
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- [Routing optimization]
- It seeks routes that minimize travel distance and other costs for multiple visit points. Various variations exist depending on the conditions to be added, such as imposing a limit on vehicle loading capacity, a limit on customer visitation time, or a limit on vehicle travel time. The system can be used for a wide range of delivery operations, including home delivery, mail, garbage collection, school bus, ship, and air.
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- [Job shop scheduling]
- Find the optimal sequence of operations when multiple jobs are processed by multiple machines. Here, each job is assumed to consist of multiple operations. Job store scheduling can be varied to establish precedence between jobs, to allow for interruptions in operations, to minimize overall completion time, or to minimize delays in the delivery of each job. It can be used in situations where you want to efficiently allocate multiple resources to a job, taking into account time factors.
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- [Work shift optimization]
- Create work shifts that meet labor standards and individual employee requirements while keeping labor costs as low as possible. By setting up the objective function and constraints, the system can be used to create employee shifts for various types of businesses. For example, you can create shifts that equalize the workload among employees or ensure that less experienced employees are paired with veterans.
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- [Other examples]
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- Resource allocation : Seek to allocate resources and effort that maximize profit.
- Production planning : Find the production volume that minimizes production and inventory costs while satisfying demand.
- Loading optimization : Seek the most compact way to pack cargo into containers.
- Portfolio selection: Seeks the allocation of funds that minimizes risk for each investment.
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