Innovative supply chain optimization models with multiple uncertainty factors

Uncertainty is an inherent factor throughout the whole supply chain (SC) channel within production, distribution, transportation, and market sales. In traditional manufacturing processes, stochastic capacity, random yield, and uncertain transportation delay are regarded as the main causes of supply uncertainty. Market fluctuations, brought on by ever-changing customer preferences and competitive marketing environments, also expose the demand side to a high level of uncertainty. Another type of uncertainty comes from unexpected disruptions, such as earthquakes, economic crises, strikes, terrorist attacks, etc., which have damaged several SC operations severely. Well-known examples include Ericsson losing 400 million euros after their supplier’s semiconductor plant caught fire in 2000, and Apple losing many customer orders during a supply shortage of DRAM chips after an earthquake hit Taiwan in 1999. The recent March, 2011, earthquake in Japan, which triggered a massive 23-foot tsunami and a nuclear crisis, even led to a global supply disruption. As a result, focusing on specific sources of uncertainty, many researchers have developed optimization models with a goal of mitigating the respective SC uncertainty and the associated risk.