Advanced Materials Research Vols. 201-203

Abstract: In this paper, a single-machine scheduling problem with simple linear deterioration was explored. By simple linear deterioration, we mean that the processing time of a job is a simple linear function of its execution starting time and its deterioration rate. The objective of this study was to find a schedule that minimizes the absolute value of maximum lateness, where the due date of jobs are a common due date. Given that the cases of common due date is a given constant and variable, we showed that the problem can be solved in polynomial time, respectively. Some extensions of the problem were also delineated.

Abstract: Growing concern in China has arisen about risks and risk management. China's iron and steel industry has been of primary importance in Chinese national economy. Studies on risks and risk management in Chinese iron and steel enterprises are rare, however. A model of risk sources based on resource ecological economics and eco-industry theory is built up, and the risk factors are analyzed in this paper. Measures contain a circular and dynamic risk management process model, a risk management integration model, and creating a risk management culture, which will help seize potential risk opportunities, take precautions against risks and mitigate risk losses. The enterprises’ performance would benefit from the new ERM process model and measures.

Abstract: This paper proposes a decision-making model of the planning quantity put into production for Make-To-Order (MTO) companies with capacity constraint. The low repeatability and the uncertain products eligibility-rate of the MTO production systems are fully taken into account, and an optimal solution is presented. Finally, a numerical example is given to illustrate the validity of the model.

Abstract: Numerous real-world problems relating to flow shops scheduling are complex. The main problem is that the solution space is very large and therefore the set of feasible solutions cannot be enumerated one by one. Current approaches to solve these problems are metaheuristics techniques, which fall in two categories: population-based search and trajectory-based search. Because of their complexity, recent research has turned to genetic algorithms to address such problems. In this paper we present an effective hybrid approach based on genetic algorithm (GA) for minimizing the number of tardy jobs in a flow shop consisting of m machines. Jobs with processing times and due dates randomly arrive to the system. We assume that job arrival or release dates are not known in advance. The objective is to minimize the number of tardy jobs. Although genetic algorithms have been proven to facilitate the entire space search, they lack in fine-tuning capability for obtaining the global optimum. Therefore the proposed approach incorporates a fitness functions and a population trained by a local improvement search based on tabu search with a candidate list strategy into GA for the problem which belongs to NP-hard class. Experimentation results show that the number of cells and the crossover strategy adapted affect the number of tardy jobs found. The results also indicate that hybrid genetic algorithm approach improves the solution quality drastically.

Abstract: This paper concentrates on modeling the vehicle routing to develop an evacuation plan for transit-dependent residents during emergency situation. Planning of transit route in the evacuation is formulated as a vehicle routing problem with time windows (VRPTW). An intelligent algorithm, in which genetic algorithm is embedded with simulated annealing is developed to solve the optimization model. A real evacuation network on which 19 pick-up points and 4 shelters are distributed is used to study the proposed evacuation strategy. The relevant results show the feasibility of the mathematical model as well as the efficiency of the solving algorithm.

Abstract: Customized Supply Chain Management (CSCM) has been made much account of attention in Flexible Manufacturing Systems (FSM). Products are customized by customer’s special needs at stochastic time. Then Manufacturing Oriented to Customization (MOC) would inevitably be faced by those enterprises that had to meet the changeable and complex needs of customers. However, there were large quantities of difficulties would appear in MOC supply chains, such as information overload, technology and resource constraints. All of these problems made it hard to quickly and effectively respond to customers’ needs. Therefore, we need to find a new way to deal effectively with the problems about how to respond quickly to supply chains oriented to customization. Petri Nets have been extensively used for modeling and simulating of the dynamics of flexible manufacturing systems. However, Petri Nets have not been very popular for molding of workflow in CSCM environmental. In this paper Stochastic Timed Petri Nets (STPN) were used to solve the above problems. The enterprises’ workflow was analyzed, and then the STPN model was constructed according to the characteristics of its internal supply chain. In order to minimize total tardiness time of workflow, the structure of STPN was optimized in a proper way. The results suggest that the STPN approach is also valid to minimize due date of each transition in CSCM and responses to customized needs more quickly than before.

Abstract: The simulation, modeling and analysis of manufacturing systems for performance improvement have become increasingly important during the last few decades. This paper presents a practical solution to a manageable and well distributed work in process (WIP) control system with simulation experiment demonstrated by constructing the virtual production lines, addressing issues such as wafer kitting strategy, critical work in process level setting. The simulation WIP instances are coordinated and synchronized with production line influence factors and activities imported. Through the testing and actual practice, this simulation tool helps semiconductor assembly and test factory production managers effectively manage work-in-process (WIP) levels to compensate the impact of unexpected production variations and achieve better factory performance.

Abstract: In this study, a new multi-motor synchronous based on adjacent coupling error and sliding mode theory is designed, the tracking error and synchronization error convergence which are proved very well by Lyapunoy theory and LaSalle's Invariance Principle, Simulation results of the synchronized system shows that the synchronization controller can effectively achieve the synchronization with a quick convergence rate and good robustness.

Abstract: A revenue coordination problem of supply chain based on lead time compression is discussed. The coordination problem involves in a supply chain consisted of a manufacturer, a third-party logistics and a vendor. The vendor implements a lot-partitioning supply model. The third-party logistics undertakes the delivery. The supply chain gains Lead time compression with lead time crashing. According to different cooperative modes, Stackelberg leader-follower game models are established to gain the optimal costs of the buyer, the vendor and the supply chain system. A decision principle is designed to compare the cost savings of the buyer, the vendor, the third-party logistics and the system. A best mode is singled out according to the decision principle.

Abstract: Practical performance optimization of a cross-docking center has been rare in the literature so far. The measures representing operation efficiency are average inventory level and transportation cost rate, while average backorder level represents the customer service level. In this paper, a simulation optimization problem is considered and a solution framework has been developed by integrating simulation, genetic algorithm (GA) and smart computing budget allocation (SCBA) to find an optimized solution. Moreover, supply disruptions are considered in the simulation model. This problem has huge search space even for medium-sized problem scenarios. To address this difficulty, the framework employs simulation to estimate the performance measures, GA to search for better design and SCBA to efficiently allocate the simulation budget.