scholarly journals Joint production planning, pricing and retailer selection with emission control based on Stackelberg game and nested genetic algorithm

2020 ◽  
Vol 161 ◽  
pp. 113733
Author(s):  
Linda L. Zhang ◽  
Gang D.U. ◽  
Jun W.U. ◽  
Yujie M.A.
Author(s):  
Gede Agus Widyadana ◽  
Nita H. Shah ◽  
Daniel Suriawidjaja Siek

Supplier has many schemes to motivate retailer to buy more and of them one is a progressive permissible delay of payment. Instead of analyst from the retailer side alone, in this chapter, we develop the inventory model of supplier and retailer. In reality, some suppliers and retailers cannot have collaboration and they try to optimize their own decision so we develop a Stackelberg Game model. Two models are developed wherein the first model supplier acts as the leader and in the second model, the retailer acts a leader. Since the models are complex, a hybrid Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) is developed to solve the model. A numerical analysis and sensitivity analysis are conducted to get management insights of the model. The results show that a Stackelberg Game model for progressive permissible delay of payment is sensitive in varies values of the first and second delay interest rate if supplier acts as a leader. The retailer gets less inventory cost when he acts as a leader compared to when vendor acts a leader at high interest rate of the first and second delay period.


2019 ◽  
Vol 25 (2) ◽  
pp. 236-252 ◽  
Author(s):  
Lin Wang ◽  
Zhiqiang Lu ◽  
Xiaole Han

Purpose This paper integrates condition-based maintenance (CBM) with production planning in a single-stage production system that deteriorates with usage during a specified finite planning horizon. The purpose of this paper is to develop an integrated production and maintenance model to minimize the expected total cost over the horizon. Design/methodology/approach A joint production planning and CBM model is proposed. In the model, a set of products must be produced in lots. The system degradation is a stationary gamma process and the degradation level is detected by inspection between production lots. Maintenance actions including imperfect preventive maintenance (PM) should be taken when the failure risk exceeds the maintenance threshold. A fix-iterative heuristic algorithm is proposed to address the joint model. Findings The proactive policy expressed as a prognosis maintenance threshold is introduced to integrate CBM with batch production perfectly. Experiments are carried out to conduct sensitivity analysis, which provides some insights to facilitate industrial manufacturing. The superiority of the proposed joint model compared with a separate decision method is demonstrated. The results show an advantage in cost saving. Originality/value Few studies have been made to integrate production planning and CBM decisions, especially for a multi-product system. Their maintenance decisions are usually based on a periodic review policy, which is not appropriate for batch production system. A prognosis maintenance threshold based on system condition and production quantity is suitable for the integrated decisions. Moreover, the imperfect PM is taken into consideration in this paper. A fix-iterative algorithm is developed to solve the joint model. This work forms a proactive maintenance for batch production.


2019 ◽  
Vol 150 ◽  
pp. 603-608 ◽  
Author(s):  
S.L. Podvalny ◽  
M.I. Chizhov ◽  
P.Y. Gusev ◽  
K.Y. Gusev

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