Abstract

Volatile markets and uncertain deterioration rate make it extremely difficult for manufacturers to make the quantity of saleable vegetables just meet the fluctuating demands, which will lead to inevitable out of stock or over production. Aggregate production planning (APP) is to find the optimal yield of vegetables, shortage and overstock symmetry, are not conducive to the final benefit.The essence of aggregate production planning is to deal with the symmetrical relation between shortage and overproduction. In order to reduce the adverse effects caused by shortage, we regard the service level as an important constraint to meet the customer demand and ensure the market share. So an uncertain aggregate production planning model for vegetables under condition of allowed stockout and considering service level constraint is constructed, whose objective is to find the optimal output while minimizing the expected total cost. Moreover, two methods are proposed in different cases to solve the model. A crisp equivalent form can be transformed when uncertain variables obey linear uncertain distributions and for general case, a hybrid intelligent algorithm integrating the 99-method and genetic algorithm is employed. Finally, two numerical examples are carried out to illustrate the effectiveness of the proposed model.

Highlights

  • We assume that all uncertain variables obey linear uncertain distribution, the equivalent crisp form can be obtained by uncertainty theory [20]

  • This paper proposed an aggregate production planning (APP) model for vegetables under the condition of allowed stockout and considering the service level constraint from the point of the manufacturer in an uncertain environment

  • In accordance with the characteristics of the APP problem for vegetables, the deterioration rate, market demand and other factors are described by uncertain variables

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. In 2016, a production planning model considering uncertain demand using two-stage stochastic programming in a fresh vegetable supply chain context was presented by Jordi Mateo et al [11]. In 2016, Xiong [19] studied the Pareto optimal area of the perishable product order timing by means of the service level and discussed a two-echelon supply chain which was comprised of a supplier and a retailer. It is very necessary to consider the service level as an important factor to study the supply chain of perishable products. Pang and Ning [28] used uncertainty theory to study the aggregate production planning problem for vegetables from the point of manufacturers.

Problem Description
Objective Function
Service-Level Constraint
Inventory Capacity Constraint
Solving Method
Equivalent Crisp Form
Genetic Algorithm Combined with 99-Method
Numerical Examples
Conclusions
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