A service-oriented framework for agent-based simulations of collaborative supply chains

Dorigatti, Mariana; Guarnaschelli, Armando; Chiotti, Omar; Salomone, Enrique

doi:10.1016/j.compind.2016.09.005

Cited by 24 publications

(10 citation statements)

References 15 publications

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“…While DES is especially useful to simulate certain elements of a supply chain, such as a port terminal Cimpeanu (2014), ABMS is a very powerful tool when the simulation reaches a wider scope. An interesting example is the work conducted by Dorigatti et al (2016), where a generic, versatile and systematic method is presented to model and transport interactions in supply chains is simulated using an agent based approach.…”

Section: Agent Based Simulation Applied To Supply Chainsmentioning

confidence: 99%

“…In this work, Dorigatti et al (2016) presents three kinds of agents: Client, Transport and Supplier. Both Client and Supplier are arranged in a georeferenced network while Transport moves from one agent to the other.…”

Section: Agent Based Simulation Applied To Supply Chainsmentioning

confidence: 99%

“…First, this work reviews some concepts regarding soy and corn supply chains in Brazil in order to gather information on its main agents and their relationships. Next, there is the definition and delimitation of the main players in this environment, which is used to shape a conceptual model, describing the model's topology and agent's interactions in a generic supply chain, similar to the one presented by Dorigatti et al (2016).…”

Section: Framework Definitionmentioning

confidence: 99%

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Application of Agent Based Simulation to analyze the impact of tax policy on soybean supply chain

Rosis

Mesquita

2018

BJO&PM

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This work seeks to explore and demonstrate the use of Agent Based Simulations (ABS) in modelling and simulating supply chains. Such methodology was applied to develop a model to evaluate the impact of current tax policies in soy supply chain in Brazil. The model brought interesting insights on how the country’s current tax structure induces logistics and tributary trade-offs, therefore generating a suboptimal grain distribution. This is accomplished by going through the conception and implementation of an Agent Based Model. First there is the definition and delimitation of the main agents acting upon soy’s supply chain, such as producers, trader and consumers. Those agents then have their behaviors studied and translated into programable patterns. Finally, the model considers the environmental interactions with the mentioned players, including the effects of infrastructure capacities, transportation costs, storage costs and tax legislation. After quantitative and behavioral validation, the simulation is then able to mimic the actual allocation of corn, soy and soymeal productions in their respective supply chains. This would allow inferring how the system could work in different tax conditions, thus quantifying the tributary impact in terms of congestions, idle infrastructure and delays. The analysis of such results points out that a path dependant tax system may induce agents to opt for inefficient logistic solutions, if such alternatives are cheaper when taking taxes into account. From those simulations it is possible to conclude that there are opportunities for supply chain efficiency gains in the design of a new tax policy.

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Section: Agent Based Simulation Applied To Supply Chainsmentioning

confidence: 99%

Section: Agent Based Simulation Applied To Supply Chainsmentioning

confidence: 99%

Section: Framework Definitionmentioning

confidence: 99%

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Application of Agent Based Simulation to analyze the impact of tax policy on soybean supply chain

Rosis

Mesquita

2018

BJO&PM

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“…Heuristic optimization methods are used to solve NPhard problems of supply chains: integrated supply chain problems can be solved by hybrid algorithms [7], graph-theorybased heuristic supports responsive supply chain design [8], and inventory routing and pricing problems in a supply chain can be solved with Tabu Search [9]. Simulation-based methods support the optimization of deterministic and stochastic models in the field of transportation [10], collaboration analysis for jointly working members [11], and supply chain optimization to find the core parameters of supply chain strategies to ensure cost efficiency [12]. Decision support systems make it possible to find optimal solutions for resource scheduling in supply chain [13] and group decision-making is an effective tool for facility location problems of supply chains [14].…”

Section: Research On Supply Chainmentioning

confidence: 99%

“…There has recently been an Complexity 3 increased interest in performance analysis of supply chains [1][2][3][4][5][6][7][8][9][10][11][12][13][14] and some recent analysis has been targeted specifically towards the integration of consignment stores into supply chain processes [15][16][17][18][19][20][21] and optimization with metaheuristics based on swarming algorithms [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40], especially black hole optimization. Firstly, the relevant terms were defined and the initial searches were conducted.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

Bányai

Illés

2017

Complexity

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The globalization of economy and market led to increased networking in the field of manufacturing and services. These manufacturing and service processes including supply chain became more and more complex. The supply chain includes in many cases consignment stores. The design and operation of these complex supply chain processes can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on metaheuristic algorithms. This research proposes an integrated supply model based on consignment stores. After a careful literature review, this paper introduces a mathematical model to formulate the problem of consignment-store-based supply chain optimization. The integrated model includes facility location and assignment problems to be solved. Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. The sensitivity analysis of the heuristic black hole optimization method is also described to check the efficiency of new operators to increase the convergence of the algorithm. Numerical results with different datasets demonstrate how the proposed model supports the efficiency, flexibility, and reliability of the consignment-store-based supply chain.

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Service Supply Chain Design by Using Agent-Based Simulation

Helo

Rouzafzoon

Gunasekaran

2018

Practices and Tools for Servitization

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Supply chain management is an important function in the service delivery. It comprises of physical materials and tools needed as well as intangible operational parts. The process of designing service supply chains is a task combining the aspects of customer-server interaction, resourcing and service delivery. Operational and structure related decisions are evaluated by using key performance indicators. Agent based modelling (ABM) offers a possibility to simulate the behaviour of such system. Customers and servers can be modelled as agents obeying rules and operating in a common world. Interactions and events may occur based on agent type, geographic location or past events. ABM approach can answer what-if questions or test the limit conditions of a designed delivery system.

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A service-oriented framework for agent-based simulations of collaborative supply chains

Cited by 24 publications

References 15 publications

Application of Agent Based Simulation to analyze the impact of tax policy on soybean supply chain

Application of Agent Based Simulation to analyze the impact of tax policy on soybean supply chain

Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

Service Supply Chain Design by Using Agent-Based Simulation

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