Zhimin Chen

Optimizing green production strategies: An integrated approach

Selection of green production strategy is a critical but difficult task due to the fact that it affects not only green benefits, but also production economy. The problem is essentially multi-objective and involves dynamic and uncertain conditions. This study focused on an integrated approach to improve the analysis and facilitate decision-making process. Discrete-event simulation model was developed to capture production flow and decision logic under real world conditions. A multi-objective genetic algorithm (MOGA), combined with improving heuristics, was developed to search the best solutions (Pareto optimums). The two modules are integrated to work in evolutionary cycles to achieve the optimization. Experiments were designed and carried out via a prototype system developed to verify and validate proposed concepts, including sensitivity analysis of related model parameters.

Simulation based analysis for selection and evaluation of green manufacturing strategies

Evaluation and selection of green sustainable development (GSD) strategies is a critical but difficult process involving many uncertain factors and affected by dynamic conditions. The decision problem is essentially multi-objective. This research proposed a simulation based method that uses simulation to capture the complicated process flow and decision logic involved, and interface the simulation with a search procedure to improve solutions. The design of simulation model emphasized a robust structure that represents adequately the process flow and decision logic of typical applications of GSD improvement. A process/activity based cost structure was built into the simulation to capture essential trade-offs contributed by different cost drivers during the process of GSD implementation. Experiments were designed and implemented via simulation to verify and validate proposed concepts. An analysis of response surface method (RSM) was conducted to illustrate the search for optimal solutions under relaxed conditions, which showed the potential of developed research.

Enterprise behaviour under Cap-and-Trade conditions: an experimental study with system dynamic models

Operating under Cap-and-Trade programme conditions has brought new challenges to industrial organizations pursuing green sustainable development by imposing more constraints on resource/energy acquisition and disposition in order to reduce green-house-gas emissions. New factors due to the conditions interact with each other and system production/service functions, causing complicated dynamic relationships that significantly affect the overall performance of participating enterprises. Managers now have to balance production economy and green improvement. This research shows a proactive approach based on system dynamics modelling to represent such complex systems and analyse the relationship to explore the underlining logic that drives system behaviour under related conditions. The analysis provides useful insights for decision or policymakers to pursue environmentally friendly and economically sound production. Conceptual models were developed and verified for functions, and simulation experiments were designed to implement the models and compare different strategies to analyse their impact on the system’s overall performance, such as long-term over-emission, continuous green investment on emissions reduction, and cost of purchasing emissions allowance or paying penalty (via over-emission tax).

A simulation optimization framework for shipment planning at RDC considering time and quantity consolidation with uncertain demands

Shipment planning (SP) at regional distribution center (RDC) involves order consolidation and vehicle routing decisions under uncertain demands, which is generally very hard to be solved by traditional analytical methods such as mathematical programs. To cope with the complexity of this important problem existing in logistics systems, a general-purpose simulation optimization framework is proposed. Discrete-event simulation (DES) is employed to model the complicated shipping processes and capture the systems dynamics and uncertainties. A new policy (ID-policy) considering time and quantity consolidation is developed to improve consolidation effectiveness. The consolidated orders and systems performance obtained by simulation are then transformed as input into a genetic algorithm designed to optimize the vehicle routes via evolutionary computation. Experiment results show that the ID-policy outperforms traditional consolidation policies such as T-policy, Q-policy and D-policy under different conditions. The proposed simulation optimization framework is also validated by the exemplary case.

Multi-agent based simulation of carbon emissions trading market in China

With the development of international carbon emissions trading market, the establishment of carbon trading market is an inevitable trend in China. This research aims to analyze a hypothesized carbon emissions trading market by using multi-agent based system simulation. Multi-agent based modeling simulates the behaviors of interacting and autonomous agents and their impact. In our study, the software-Anylogic© is used to build a model which contained 100 agents (enterprises) interacting with one another in an emission-quote trading market as autonomous decision makers. These agents act as buyers or sellers. A market-control agent directs the trading between the buyer and seller agents and enables a market mechanism with dynamic auction.

Implement green improvement or buy emission permit? A cost-benefit analysis under Cap-and-Trade environment

To reduce carbon emission more efficiently and effectively, Cap-and-Trade (C&T) and some compulsory environmental regulations are gradually implemented around the world, which brings huge challenges to generating companies. How to balance between production quantity, green improvement and carbon trade under C&T condition becomes an important decision for generating companies. A non-linear programming model considering uncertain demands is proposed in this paper to implement a cost-benefit analysis for the generating companies. Our research results show that with the increase of carbon price, the optimal production quantity and the actual carbon emission drop down. The optimal investment of green improvement is an increasing function of carbon price. However, the emission quota has only impact on the transaction quantity of emission permit in the carbon market. It has nothing to do with the optimal production quantity and investment of green improvement.

Simulation modeling and analysis for ordering decision of manufacturer with supply, demand and exchange rate risks

Ordering decision-making in global supply chain faces more risks such as the uncertainties of supply, demand and exchange rate. A multi-stage, stochastic, non-linear programming model is proposed to describe this problem. Due to its complexity, discrete-event simulation is used to capture the stochastic and dynamic characteristics, and evaluate the systems performance. A response surface method integrating with simulation and ranking selection is designed to optimize the ordering quantities. The results of simulation experiments validate the model and optimization procedure proposed in this paper.

Analysis and optimization of the picking up medicine queuing system for a medical warehouse - a case study of Shenzhen Jianhua Medical Company

This paper, based on the warehouse operations of Shenzhen Jianhua Medical company, describes the elements of the picking up medicine queueing system, identifies the characteristics of the probability distribution of customer interarrival times and service times, determines which queueing model is most appropriate for the Jianhua company, applies M/Ms model and M/M/s nonpreemptive priorities model to obtain the key measures of performance for this queueing system, applies economic analysis to decide how many servers should be provided to minimize the total cost, and gives the optimal design to improve the behavior of the warehouse operations for Jianhua Company.