The objective of this paper is to develop an easily understood methodology for solving stochastic, multi-criteria LP problems in spreadsheets. Additionally, relatively little work has focused on devising general solution procedures for optimization problems that are both stochastic and multi-criteria in nature. Unfortunately, most of the resulting solution techniques are not easily understood by, available to, or implemented by practitioners in the business world. A similar level of effort has been devoted to challenging problems in multi-criteria optimization. A significant amount of research has been directed at developing techniques for solving stochastic programming problems.
Īs managerial DMs become increasingly aware of the availability and purpose of the solver optimization software built into today's spreadsheets, questions about how to use this software with decision problems involving stochastic parameters and multiple criteria will likely emerge. In these situations, multi-criteria optimization techniques must be used to allow DMs to properly model and analyze the trade-offs inherent with multiple conflicting objectives. The inherent non-commensurate and conflicting nature of these pressures often makes it difficult or impossible to formulate a single objective function for many real-world decision problems. This is complicated by the fact that today's information-rich business environment imposes numerous competitive, political, financial, environmental, and societal pressures on DMs. Įffectively modeling the uncertainties in a stochastic LP model is a challenging yet necessary step in evaluating the robustness of a potential “optimal” solution to simultaneous changes in estimated parameter values. When one or more parameters in an LP problem are represented by a random variable, a stochastic LP problem results. As a result, some degree of randomness or uncertainty is likely to impact the parameter estimates used in medium- to long-term LP planning models and may also affect short-term models. Unfortunately, uncertainty in such things as costs, demand, interest rates, production yields, and equipment reliability is the practical reality faced by business decision makers (DMs) on a daily basis. Over the past several decades, numerous applications for LP have been proposed for improving the efficiency of business operations. Sub Insurance_Check()ĪctiveSheet.Range("$A$2:$K$25720").AutoFilter Field:=11, Criteria1:= _ĪctiveSheet.Range("$A$2:$K$25720").Linear programming (LP) is a mathematical programming technique designed to optimize a (single) linear objective function subject to a linear constraint set where all model parameters are assumed to be known with certainty. Then next should be the values for "Sample Insurance2" and so on. If in Sheet2, Cell A1 I have "Sample Insurance1" I should have a return on sheet two with all of the values from sheet1 that are "Sample Insurance1".
You can see that under insurance claim, are sample insurance 1, 2, and 3. I had to include a picture unfortunately.
I'd appreciate your help!Įdit1: look below the code for context. I've changed the data from the insurance number to "ABC" on the first occurrence, and "123" on the second occurrence. The problem is that when I record the macro, I'm copying the information in cell A1 and not Cell A1. I tried recording a macro, and this is what I have below. Then the macro should go to sheet2 Cell A2 and continue this process until I've exhausted all of the insurance numbers in sheet2 cells A1:A500. Essentially I'm trying to have the macro look at cell A1 in sheet2, then compare that insurance number with all of the occurrences on sheet one and copy the data into sheet2. On sheet1 is the insurance number and additional information that needs to come over to sheet2.
On sheet2, I have a column of insurance numbers in rows A1:A500. I've used the range command but it hasn't worked. I've tried figuring out how to make cell A2 static, and pull directly. Here is my problem, and I am trying to build a macro to solve this.