SBIR Phase I: Advertising Sales and Traffic Optimization: Difficult Customer-Requested Optimization Constraints and Scalability on Real Data

该SBIR第一阶段项目建议开发一种新的优化引擎，该引擎支持潜在客户所要求的重要分配约束，并使用新技术和真实的客户数据使其可扩展。在丰富的表现力下确定谁从谁那里购买什么物品是一个可证明的困难优化问题，需要复杂的算法。私家侦探？学术小组已经开发了新的树搜索/整数规划以及自动化问题（重新）制定的技术，他们已经适应了它，以满足广告市场的需求。拟议的工作包括开发新的优化技术。更广泛的/商业影响涉及显着的效率提高-即，在一个巨大的行业中，改善分配，使买卖双方受益。美国电视广告市场每年为750亿美元。将类似于本文所提出的方法部署到其他市场的经验表明，效率提高了12% - 41%。效率的提高将大大增强美国的竞争力。结构化、优化的市场带来了更公平的竞争环境和更广泛的准入--对新进入者也是如此。消费者也会受益，因为他们会看到更相关的广告，而不是让他们的时间和注意力被不相关的广告占据。广告市场的入口是一个单一的卖家，多个买家的设置。后来足迹可以推广到表达的交流。这种方法和技术也适用于其他市场，如电力和污染权市场。所提出的优化技术也适用于市场以外的应用。该公司计划通过学术渠道、课程、行业联系人和政府联系人广泛传播研究结果。他们还将计划吸引少数民族和本科生。这一努力描述了创新生态系统和拟议项目之间的共生关系。

This SBIR Phase I project proposes to develop a new optimization engine that supports important allocation constraints requested by potential customers, and make it scalable using novel techniques and real customer data. Determining who buys what items from whom under rich expressiveness is a provably hard optimization problem that requires sophisticated algorithms. The PI?' academic group has developed technology for novel tree search / integer programming as well as automated problem (re)formulation, and they have adapted it to address the advertising market's needs. Proposed work includes developing new optimization techniques.The broader/commercial impact involves a significant efficiency improvement - i.e., improvement in the allocation that benefits both buyers and sellers - in a huge industry. The US TV ad market is $75 billion annually. Experiences from deploying approaches similar to that proposed here into other markets suggest 12% - 41% efficiency improvements. The efficiency gains will significantly enhance US competitiveness. The structured, optimized market begets a fairer playing field and broader access - also for new entrants. Consumers also benefit because they will see more relevant ads rather than having their time and attention taken by irrelevant ones. The on-ramp to the advertising market is a single-seller, multi-buyer setting. Later the footprint can be generalized to expressive exchanges. The approach and technology also apply to other markets such as those for electricity and pollution rights. The proposed optimization technology applies to applications beyond markets also. The company has a plan for disseminating the results broadly via academic outlets, courses, industrial contacts, and government contacts. They will also plan to engage minorities and undergraduates. The effort describes a symbiotic relationship between an innovation ecosystem and the proposed project.