A Multi-Agent Approach Towards Collaborative Supply Chain Management

Supply chain collaboration has become a critical success factor for supply chain management and effectively improves the performance of organizations in various industries. Supply chain collaboration builds on information sharing, collaborative planning and execution. Information technology is an important enabler of collaborative supply chain management. Many information systems have been developed for supply chain management from legacy systems and enterprise resource planning (ERP) into the newly developed advanced planning and scheduling system (APS) and e-commerce solutions. However, these systems do not provide sufficient support to achieve collaborative supply chain. Recently, intelligent agent technology and multi-agent system (MAS) have received a great potential in supporting transparency in information flows of business networks and modeling of the dynamic supply chain for collaborative supply chain planning and execution. This paper explores the similarities between multi-agent system and supply chain system to justify the use of multi-agent technology as an appropriate approach to support supply chain collaboration. In addition, the framework of the multi-agent-based collaborative supply chain management system will be presented

THE USE OF REGRESSION ANALYSIS TO DETERMINE THE ORDER OF DELAYS IN THE MANUFACTURING PROCESSES

The effect of Supply Chain Management is very important on the performance of companies their life cycle.  The paper tries to investigate the role of Supply Chain Management on company performance. Companies in order to be successful in the manufacturing sector of industries, they need to manage the data order and the performance of the company. Therefore, this paper tries to emphasize that the order parameters help in estimation of the order implementation during deadlines. Thus, the obtained results will provide insights to companies on manufacturing industries and to decision makers. The results will also help decision makers to be more accurate on their decisions about orders and reaching the results by the model

Pergerakan predator untuk mengejar mangsa dinamis menggunakan D* Lite berbasis algoritma pathfinding

Pergerakan agen pada permainan Real Time Strategy dipengaruhi oleh beberapa faktor salah satunya adalah teknik pergerakan agen didalam lingkungan permainan. Pathfinding dalam video game merupakan algoritma kecerdasan buatan bagaimana cara sebuah agen bergerak menemukan jalan optimal dengan usaha minimal sampai pada tujuan. Hal ini bisa dicapai dengan mengimplementasikan suatu algoritma pathfinding pada game. Penelitian ini mengenai algoritma D* Lite yang mampu merencanakan pencarian jalur di lingkungan game dengan environment yang berubah sekaligus objek yang sebagai target bergerak dan menjadikan proses pengejaran target menjadi efisien bagi agen serta memberikan dasar yang kuat untuk penelitian lebih lanjut tentang metode pencarian ulang dalam kecerdasan buatan. ========================================================================================================= The movement of agents in the Real Time Strategy game influenced by several factors, one of which is the technique of agent movement within the game environment. Pathfinding in a video game is an artificial intelligence algorithm how to find an agent moves the optimal way in which there are obstacles in the environment. This can be achieved by implementing a pathfinding algorithm to the game. This study of the D* Lite algorithm is able to plan a search path in a game environment, change the environment and moving target to be efficient, optimal and complete for agents and will describe some way of planning applications and provides a solid foundation for further research on methods of search re in artificial intelligence

Supply chain management untuk agen game RTS menggunakan HFSM

Real Time Strategy merupakan salah satu genre dalam permainan komputer yang memiliki ciri khas berupa permainan perang. Permainan yang menarik dan disukai biasanya hampir mendekati dunia nyata. Umumnya pada game yang ada, tidak memiliki distribusi makanan, sehingga menjadikan game kurang manusiawi. Pada model lain pasukan yang kembali dari perang, membutuhkan waktu agar pulih, namun ketika kondisi dimana pemain ingin kembali berperang, energi pasukan belum sepenuhnya pulih, karena itu dibutuhkan suatu metode agar pasokan makanan bisa tepat sasaran. Percobaan ini menggunakan metode Hierarchical Finite State Machine untuk mendesain perilaku agen game RTS dan mengacu pada skema supply chain management agar perilaku agen dalam mendistribusikan makanan mendekati dunia nyata. Penempatan lokasi koordinat agen dirancang mengacu pada skema supply chain dengan pendekatan gravity location model agar menghasilkan posisi koordinat yang optimal sehingga waktu dan biaya dalam distribusi makanan bisa diminimalkan. Hasil pengujian menunjukkan rata-rata penghematan biaya dan waktu masing – masing adalah 52.97% dan 48.47 %. ========================================================================================================= Real Time Strategy is one of the genres in computer games that have a characteristic form of war. The attractive and preferably game usually approach to the real world.Generally on RTS games do not have food distribution that makes the game less humane. On other models troops was returning from war, need to takes recovered, but when the condition that the player wants to war again, the energy not fully recovered, so need a method that the food supply target is precise. This experiment using Hierarchical Finite State Machine to design the behavior of agents and refers to the scheme of supply chain management so that the behavior approach to the real world. Placement agent location coordinates using a scheme of supply chain approach to gravity location coordinates of the model in order to produce an optimal position so that the time and costs in the food distribution can be minimized. The results show the average percentage cost and time savings for 52.97% and 48.47%

Supply chain complexity and robustness analysis

Imperial Users onl