scholarly journals An Uncertain APP Model with Allowed Stockout and Service Level Constraint for Vegetables

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2332
Author(s):  
Yufu Ning ◽  
Na Pang ◽  
Shuai Wang ◽  
Xiumei Chen
Keyword(s):  
Production Planning ◽  
Equivalent Form ◽  
Service Level ◽  
Aggregate Production Planning ◽  
Aggregate Production ◽  
Hybrid Intelligent Algorithm ◽  
Uncertain Variables ◽  
Optimal Output ◽  
Deterioration Rate ◽  
Proposed Model

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.

scholarly journals An Uncertain Aggregate Production Planning Model Considering Investment in Vegetable Preservation Technology

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Yufu Ning ◽  
Na Pang ◽  
Xiao Wang
Keyword(s):  
Production Planning ◽  
Equivalent Form ◽  
Planning Problem ◽  
Planning Model ◽  
Aggregate Production Planning ◽  
Profit Model ◽  
Aggregate Production ◽  
Technology Investment ◽  
Preservation Technology ◽  
Preservation Technology Investment

In this paper, we study the aggregate production planning problem for vegetables within the framework of uncertainty theory. In detail, preservation technology investment is taken into consideration to reduce the deterioration rate and improve the freshness of the vegetables. Meanwhile, an expected profit model considering preservation technology investment under the capacity constraints is built, whose objective is to find the optimal yield, workforce, and preservation investment strategies. Moreover, the proposed model can be transformed into its crisp equivalent form. Finally, a numerical example is carried out to illustrate the effectiveness of the proposed uncertain aggregate production planning model.

Dual Approach to the Harmonized Model between Inventory Reduction and Heijunka (Production Leveling) based on the Minimum Average-energy Principle

2019 ◽  
Vol 01 (02) ◽  
Author(s):  
Tsuyoshi Kurihara ◽  
Takaaki Kawanaka ◽  
Hiroshi Yamashita
Keyword(s):  
Production Planning ◽  
Inventory Management ◽  
Average Energy ◽  
Optimal Solution ◽  
Exponential Smoothing ◽  
Aggregate Production Planning ◽  
Energy Principle ◽  
Dual Approach ◽  
Aggregate Production ◽  
Proposed Model

A major issue in manufacturing is the balance between inventory reduction and heijunka (i.e., production leveling). To address this issue in aggregate production planning, linear programming models that consider many factors and use “exponential smoothing” as an approximate leveling method have been mainly studied. However, this methodology has problems that may limit its use as an optimal solution approximate method, and impair the timeliness required for aggregate production planning by the complexity of these models. To solve this issue, we have been developing harmonized models to balance between lowering the inventory management energy and increasing the heijunka entropy, based on demand and inventory quantities as simple optimization models. In this study, we develop a dual approach to the previously proposed model to maximize the heijunka entropy and propose a new model to minimize the inventory management energy based on the “minimum average-energy principle.” We show that the proposed model’s inventory state is lower than that of traditional exponential smoothing through numerical experiments. This study, therefore, theoretically enables a new optimal solution to the harmonized (balancing) problem, based on the concept of entropy and energy, and practically enables aggregate production planning in a timely and simple manner.

scholarly journals A Multiobjective Fuzzy Aggregate Production Planning Model Considering Real Capacity and Quality of Products

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Najmeh Madadi ◽  
Kuan Yew Wong
Keyword(s):  
Production Planning ◽  
Customer Service ◽  
Optimal Solution ◽  
Service Level ◽  
Aggregate Production Planning ◽  
Production Lines ◽  
Aggregate Production ◽  
Customer Service Level ◽  
Quality Of Products ◽  
Parts Manufacturing

In this study, an attempt has been made to develop a multiobjective fuzzy aggregate production planning (APP) model that best serves those companies whose aim is to have the best utilization of their resources in an uncertain environment while trying to keep an acceptable degree of quality and customer service level simultaneously. In addition, the study takes into account the performance and availability of production lines. To provide the optimal solution to the proposed model, first it was converted to an equivalent crisp multiobjective model and then goal programming was applied to the converted model. At the final step, the IBM ILOG CPLEX Optimization Studio software was used to obtain the final result based on the data collected from an automotive parts manufacturing company. The comparison of results obtained from solving the model with and without considering the performance and availability of production lines, revealed the significant importance of these two factors in developing a real and practical aggregate production plan.

scholarly journals Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

2017 ◽  
Vol 5 (2) ◽  
pp. 85
Author(s):  
Kaveh Khalili-Damghani ◽  
Ayda Shahrokh ◽  
Alireza Pakgohar
Keyword(s):  
Supply Chain ◽  
Production Planning ◽  
Financial Risk ◽  
Goal Attainment ◽  
Experimental Production ◽  
Aggregate Production Planning ◽  
Aggregate Production ◽  
Multi Objective ◽  
Proposed Model ◽  
Human Resource Training

<p>In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.</p>

scholarly journals Solving Fuzzy Multiproduct Aggregate Production Planning Problems Based on Extension Principle

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Shih-Pin Chen ◽  
Wen-Lung Huang
Keyword(s):  
Production Planning ◽  
Critical Role ◽  
Solution Procedure ◽  
Performance Measure ◽  
Extension Principle ◽  
Aggregate Production Planning ◽  
Aggregate Production ◽  
Mathematical Programs ◽  
Decision Variables ◽  
Proposed Model

Aggregate production planning (APP) plays a critical role in supply chain management (SCM). This paper investigates multiproduct, multiperiod APP problems with several distinct types of fuzzy uncertainties. In contrast to the existing studies, the modelling in this work conserves the fuzziness such that the obtained APP is more effective. Based on Zadeh’s extension principle, the results obtained are fuzzy solutions described by membership functions, in contrast to results from previous studies. A pair of two-level parametric mathematical programs is formulated to calculate the lower and upper bounds of the optimum fuzzy performance measure. The membership function of the fuzzy total cost is constructed by enumerating various possibility levels. A case studied in previous research is investigated to demonstrate the validity of the proposed model and solution procedure. Because the optimal objective value and associated decision variables are expressed using fuzzy numbers rather than crisp values, the proposed approach is able to represent APP systems more accurately, and therefore, the results obtained can provide decision makers with more effective and informative APPs and more chance to achieve the optimal disaggregate plan.

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