In this paper, we have presented a new technique for solving scenario based multi-period stochastic programming problems and presented a case study for the business policy of a super shop market in Bangladesh. We have developed our technique based on decomposition based pricing method which is the latest and faster decomposition technique in use. To our knowledge, this is the first work in the field of stochastic programming for solving multi-period stochastic optimization problems by using decomposition based pricing method. We have also developed a model by collecting data of a year from a super shop market of Bangladesh and analyzed their profit by dividing the whole year into four periods for different scenarios of an uncertainty. We have developed a computer code by using mathematical programming language AMPL and analyzed the model by using our developed technique.
Sajal Chakroborty and Babul Hasan REF have proposed a technique for scenario based multi-period stochastic programming problems.
A Proposed Technique for Solving Scenario Based Multi-Period Stochastic Optimization Problems with Computer Application
International Journal of Mathematical Sciences and Computing
Computer Science