Today's industries are highly complex in nature offering multiple
customized quality products with shorter product life-cycles,
volatile demand and tighter due-dates etc. to the customers.
Manufacturers are focussing on Available-To-Promise (ATP) to their
customers as a retention strategy. In other words manufacturers are
forced to commit in advance to the customers the amount they can
deliver by the specified due-date. In the current work we address a
single manufacturer and multi-customer supply chain setting wherein
there are multiple products, stochastic demands, varying profit
rates, different learning rates etc. We restrict our focus to the
multi-product ATP (MATP) strategies that maximize net profit of the
manufacturer. We present optimization models in which there is a
possibility of cancelling prior committed orders. We also model the dynamic pricing decision integrated with revenue management in MATP setting. We
present the results of weak concavity of the MATP models and related structural
insights. We support our thesis with rigorous numerical experimental results.
Mathematics Subject Classification:
Primary: 90C90, 90C27, 90B30 ; Secondary: 90C3.
Sandeep Dulluri, N. R. Srinivasa Raghavan. Revenue management via multi-product available to promise. Journal of Industrial & Management Optimization,
Hong Seng Sim, Wah June Leong, Chuei Yee Chen, Siti Nur Iqmal Ibrahim.
Multi-step spectral gradient methods with modified weak secant relation for large scale unconstrained optimization.
Numerical Algebra, Control & Optimization,