Exercício de verificação de razoabilidade

Você está trabalhando no planejamento de produção de uma fábrica para os próximos 4 meses. Como entradas, você recebe o estoque inicial de 100 unidades, os custos fixos de operação da planta (US\(), os custos unitários de produção (US\)), os custos de armazenagem de estoque (US$), a capacidade mensal de produção e a demanda mensal.

Todas as variáveis de entrada estão em um DataFrame do Pandas chamado d e ele foi impresso para você no console. Seu objetivo é determinar se a linha de produção deve ficar ligada ou desligada, o quanto produzir e o quanto manter em estoque para atender à demanda mensal ao menor custo possível.

Este exercicio faz parte do curso

Análise de Cadeia de Suprimentos em Python

exercicio interativo prático

Transforme teoria em prática com um dos nossos exercicio interativos

Iniciar exercicio

Este exercicio faz parte do curso

Análise de Cadeia de Suprimentos em Python

IntermediárioNível de habilidade

4.8+

Comece o curso gratuitamente

Linear Programming (LP) is a key technique for Supply Chain Optimization. The PuLP framework is an easy to use tool for working with LP problems and allows the programmer to focus on modeling. In this chapter we learn the basics of LP problems and start to learn how to use the PuLP framework to solve them.

Exercise 1: Basics of optimization Exercise 2: To LP, or to not IP?Exercise 3: Choosing exercise routine Exercise 4: Basics of PuLP modeling Exercise 5: Getting started with LpProblem()Exercise 6: Simple resource scheduling exercise Exercise 7: Using lpSum Exercise 8: Trying out lpSum Exercise 9: Logistics planning problem

In this chapter we continue to learn how to model LP and IP problems in PuLP. We touch on how to use PuLP for large scale problems. Additionally, we begin our case study example on how to solve the Capacitated Plant location model.

Exercise 1: LpVariable dictionary function Exercise 2: Logistics planning problem 2 Exercise 3: Traveling salesman problem (TSP)Exercise 4: Example of a scheduling problem Exercise 5: Scheduling workers problem Exercise 6: Preventative maintenance scheduling Exercise 7: Capacitated plant location - case study P1 Exercise 8: Review data for case study Exercise 9: Decision variables of case study Exercise 10: Objective function of case study Exercise 11: Logical constraints Exercise 12: Logical constraint exercise Exercise 13: Logical constraints exercise 2

This chapter reviews some common mistakes made when creating constraints, and step through the process of solving the model. Once we have a solution to our LP model, how do we know if it is correct? In this chapter we also review a process for reasonableness checking or sanity checking the results. Furthermore, we continue working through our case study example on the Capacitated Plant location model by completing all the needed constraints.

Exercise 1: Erros comuns em restrições Exercise 2: Exercício de restrição de demanda dependente Exercise 3: Exercício de combinação de restrições Exercise 4: Localização de plantas com capacidade – estudo de caso P2 Exercise 5: Restrições do exercício do estudo de caso Exercise 6: Adicionando restrição lógica no exercício do estudo de caso Exercise 7: Resolver o modelo no PuLP Exercise 8: Escolha o status do modelo Exercise 9: Exercício: resolvendo o plano de produção Exercise 10: Verificando a razoabilidade da solução Exercise 11: Exercício de revisão da especificação do modelo Exercise 12: Exercício de verificação de razoabilidade

Exercicio Atual

In our final chapter we review sensitivity analysis of constraints through shadow prices and slack. Additionally, we look at simulation testing our LP models. These different techniques allow us to answer different business-related questions about our models, such as available capacity and incremental costs. Finally, we complete our case study exercise and focus on using sensitivity analysis and simulation testing to answer questions about our model.

Exercise 1: Shadow price sensitivity analysis Exercise 2: Sensitivity analysis exercise Exercise 3: Shadow price and slack exercise pt1 Exercise 4: Shadow price and slack exercise pt2 Exercise 5: Capacitated plant location - case study P3 Exercise 6: Solving the model case study exercise Exercise 7: Sensitivity case study exercise Exercise 8: Simulation testing solution Exercise 9: Simulation testing solution exercise Exercise 10: What is the risk exercise Exercise 11: Capacitated plant location - case study P4 Exercise 12: Simulation testing capacitated model Exercise 13: Interpreting simulation results exercise Exercise 14: Final summary