An Agent-based Simulation of a QoS-oriented Supply Chain

With adaptive customer-orientation the efficiency of supply chain management is improved substantially. By the introduction of service quality-based decision-making into supply chain management the quality of service (QoS) within supply chains is expected to improve autonomously and continuously up- and downstream. In the paper the main characteristics of quality of service oriented supply chain management are outlined. The quality of service criterion, introduced into the adaptive supply chain model, provides market regulators and managements with the needed information and feedback to their increasingly informed decisions. By an experiment comprising several typical scenarios on our agent-based simulation model it was possible to empirically verify the expected impact of quality of service-based reasoning on generic adaptive supply chains.</p

An Agent-based Simulation of a QoS-oriented Supply Chain

With adaptive customer-orientation the efficiency of supply chain management is improved substantially. By the introduction of service quality-based decision-making into supply chain management the quality of service (QoS) within supply chains is expected to improve autonomously and continuously up- and downstream. In the paper the main characteristics of quality of service oriented supply chain management are outlined. The quality of service criterion, introduced into the adaptive supply chain model, provides market regulators and managements with the needed information and feedback to their increasingly informed decisions. By an experiment comprising several typical scenarios on our agent-based simulation model it was possible to empirically verify the expected impact of quality of service-based reasoning on generic adaptive supply chains.</p

'No one in the driver's seat' : an agent-based modelling approach to decentralised behaviour in supply chain co-ordination

As decentralised supply chain networks become the norm and vertically integrated firms the exception, there is a need to better understand decentralised co-ordination in such supply chains. However, contemporary research in supply chain management proceeds under the assumption that there is always a dominant actor in the supply chain network who is ‘in the driver's seat’. This article describes a study that investigates situations in which effective industrial supply chain co-ordination is achieved by multiple, independent actors where ‘no-one is in the driver's seat’. It introduces a formal modelling method to investigate such issues, called agent-based modelling. In this, we build on the notion of complex adaptive systems. The article shows the application of this method in three experiments with an simple supply chain model in one specific agent-based simulation environment. Exploratory findings are discussed and promising areas for further research are indicated

Agent Based Modeling and Simulation Framework for Supply Chain Risk Management

This research develops a flexible agent-based modeling and simulation (ABMS) framework for supply chain risk management with significant enhancements to standard ABMS methods and supply chain risk modeling. Our framework starts with the use of software agents to gather and process input data for use in our simulation model. For our simulation model, we extend an existing mathematical framework for discrete event simulation (DES) to ABMS and then implement the concepts of variable resolution modeling from the DES domain to ABMS and provide further guidelines for aggregation and disaggregation of supply chain models. Existing supply chain risk management research focuses on consumable item supply chains. Since the Air Force supply chain contains many reparable items, we fill this gap with our risk metrics framework designed for reparable item supply chains, which have greater complexity than consumable item supply chains. We present new metrics, along with existing metrics, in a framework for reparable item supply chain risk management and discuss aggregation and disaggregation of metrics for use with our variable resolution modeling

DISAIN MITIGASI RISIKO RANTAI PASOK UMKM PRODUK PAKAIAN KOTA BANDUNG DENGAN PENDEKATAN SUPPLY CHAIN RISK MANAGEMENT.

ABSTRAK Dari 6 sektor produk UMKM kota Bandung (pakaian/fashion, makanan dan minuman, jasa, produksi, dan kerajinan/craft), produk pakaian/fashion mendominasi omzet penjualan mencapai 30,8% dari total omzet produk UMKM, Sedangkan 5 sektor lainnya hanya memberikan kontribusi rata-rata 14.0%. Dengan kata lain sektor pakaian/fashion memberikan kontribusi dua kali lipat dari rata-rata omzet sektor lainnya. Untuk menjamin kelancaran rantai pasokan UMKM pakaian tersebut maka harus ada usaha mengantisipasi atau mengurangi gangguan-ganguan terhadap aktivitas rantai pasok terutama yang akan menimbulkan risiko. Semua penyebab risiko harus dapat diidentifikasi dan diukur kemudian dilakukan mitigasi risiko tersebut. Dalam penelitian ini dilakukan identifikasi risiko dan merancang strategi mitigasi dengan menerapkan model House Of Risk (HOR), pemetaan aktivitas rantai pasok berdasarkan 5 tahap utama menggunakan model Supply Chain Operation Reference (SCOR), sedangkan penilaian risiko dilakukan dengan skala dampak risiko (severity), kemunculan risiko (occurance) model Failure Mode Effect Analysis (FMEA). Dari proses identifikasi model HOR tahap 1 ditemukan 24 kejadian risiko (risk event ) dan 24 agen penyebab risiko (risk agent), selanjutnya penerapan HOR tahap 2 diperoleh 14 aksi mitigasi untuk mengeliminir timbulnya agen risiko yang mengganggu aktivitas supply chain UMKM produk pakaian. Berdasarkan keseluruhan aksi mitigasi tersebut dihasilkan 9 aksi mitigasi sebagai disain mitigasi risiko yang dapat direkomendasikan dan diterapkan pada rantai pasok UMKM produk pakaian kota Bandung. Kata Kunci : UMKM, Supply Chain Management, Supply Chain Risk Management, Risk Event and Risk Agent, House Of Risk (HOR), Supply Chain Operation Reference (SCOR), Disain Mitigasi. ABSTRACTS From 6 Bandung SMEs (Small and Medium Micro Enterprises) sector (apparel/fashion, food and beverage, services, production, and craft), products of clothing/fashion dominates sales turnover reached 30.8% of the total turnover of the products of SMEs , while 5 other sectors only give contributed an average of 14.0%. In other words sectors of the clothing/fashion contributes twice that of the average turnover of other sectors. To ensure the smooth running of the apparel supply chain SMEs there should be efforts to anticipate or mitigate interference-disturbance of the activity of the supply chain that would pose a risk especially. All causes of risk should be identified and measured subsequently carried out the risk mitigation. In this research, the identification of risk and devise mitigation strategies by applying the model House Of Risk (HOR), mapping the activity of the supply chain based on five main stages using a model Supply Chain Operations Reference (SCOR), while the risk assessment carried out by the scale of the risk impact (severity), the emergence of risk (occurance) model of Failure Mode Effect Analysis (FMEA). HOR models of the identification process stage 1 found 24 risk events (risk event) and 24 the causative agent of risk (risk agent), then the implementation of HOR phase 2 obtained 14 mitigation actions to eliminate the risk of the emergence of agents that interfere with the activity of SMEs supply chain clothing products. Based on the overall mitigation actions are generated 9 mitigation actions as a design risk mitigation can be recommended and implemented in the supply chain clothing products SMEs Bandung. Keywords : SMEs, Supply Chain Management, Supply Chain Risk Management, Risk Event and Risk Agent, House Of Risk (HOR), Supply Chain Operations Reference (SCOR), Design Mitigation

An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems

Most solutions to the inventory management problem assume a centralization of information that is incompatible with organisational constraints in real supply chain networks. The inventory management problem is a well-known planning problem in operations research, concerned with finding the optimal re-order policy for nodes in a supply chain. While many centralized solutions to the problem exist, they are not applicable to real-world supply chains made up of independent entities. The problem can however be naturally decomposed into sub-problems, each associated with an independent entity, turning it into a multi-agent system. Therefore, a decentralized data-driven solution to inventory management problems using multi-agent reinforcement learning is proposed where each entity is controlled by an agent. Three multi-agent variations of the proximal policy optimization algorithm are investigated through simulations of different supply chain networks and levels of uncertainty. The centralized training decentralized execution framework is deployed, which relies on offline centralization during simulation-based policy identification, but enables decentralization when the policies are deployed online to the real system. Results show that using multi-agent proximal policy optimization with a centralized critic leads to performance very close to that of a centralized data-driven solution and outperforms a distributed model-based solution in most cases while respecting the information constraints of the system

Supply Chain Service Quality Improvement by E-marketplace Automation

E-marketplaces have become an essential part of e-commerce. In our research, a decentralized agent-based e-marketplace platform was devised. Although there are significant agent-based supply chain models in the literature, measuring quality performance using agents is still a subject of investigation. In order to improve overall supply chain service quality by allowing companies' agents to evaluate the service quality of their partners through the history of their transactions, this article proposes a service quality agent model. The model is designed using MCDM tools to suit different approaches to supply chain management. Consequently, since more informed procurement decisions are taking place continuously and autonomously at each node of a supply chain, supply chain service quality is being improved along the whole supply chain. At the end, the service quality valuation model of the supply chain is empirically evaluated

Agent-based modelling of offshore upstream petroleum logistics

Faced with dwindling oil prices, the petroleum industry now needs to economize its operations. A case study of upstream petroleum logistics, the management of supplies to and from petroleum platforms and rigs, is used to describe current logistics and supply chain management (SCM) challenges facing these operations in Norway. The provided case narrative reveals how an integrated planning system used to co-ordinate operations is proven relatively difficult to implement and use. As alternative research approach agent-based modelling (ABM) is applied and discussed in association with actor network theory in a SCM business-functional setting to theoretically ground use of ABM as methodology. An empirically-grounded conceptual model, the first stage of ABM methodology, is created for petroleum logistics. Findings from this first stage of inquiry also suggest how and why ABM is applicable in petroleum logistics and SCM. Keywords: actor network theory, agent-based modelling, petroleum logistics, supply chain management.publishedVersio