Question: Part 2 : Goal Programming for Multi - Objective Decision MakingBuilding on the previous linear programming model, Green Tech Solutions now wants to incorporate multiple
Part : Goal Programming for MultiObjective Decision MakingBuilding on the previous linear programming model, Green Tech Solutions now wants to incorporate multiple objectives into their decisionmaking process. They've identified several goals, some of which may conflict with each other. The company wants to use goal programming to find a satisfactory solution that balances these objectives.Goals:Profit Goal: Achieve a total profit of at least $Production Volume Goal: Produce at least units in total across all product linesSustainability Goal: Limit raw material usage to kg or lessLabor Utilization Goal: Use at least labor hours to maintain workforce stabilityHighTech Focus Goal: Ensure that the number of energyefficient laptops and smart thermostats produced is at least of the total productionConstraints:Keep all constraints from Part Goal Programming Formulation:For each goal, introduce positive and negative deviational variables d and d to represent over and underachievement of the goalProfit Goal: xxxxx dn dp Production Volume Goal: x x x x x dn dp Sustainability Goal: xxx xx dn dp Labor Utilization Goal: xxx xx dn dHighTech Focus Goal: xxxxx dn dp Objective Function:Minimize Z wdn dp wdn dp wdp dn wdn wdnWhere w w w w and w are weights assigned to each goal based on their relative importance to the company.Tasks for Part :Discuss the potential conflicts between the different goals and how goal programming can help address these conflictsFormulate the complete goal programming model, including all constraints from Part and the new goal constraintsAssign weights to each goal based on a hypothetical priority structure for Green Tech Solutions. Justify your choice of weightsSolve the goal programming model using appropriate softwareInterpret the results, focusing on: a Which goals were fully achieved, partially achieved, or not achieved? b What tradeoffs were made between different goals? c How does the solution compare to the original linear programming solution?
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