A pragmatic approach for optimal selection of plant-specific process plans in a virtual enterprise

Feng, Di; Yamashiro, Mitsuo

doi:10.1016/j.jmatprotec.2005.11.026

Cited by 17 publications

(11 citation statements)

References 15 publications

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“…Feng et al [12] and Cao et al [13] have proposed a solution as to how to select partners while considering the factors of cost, due date and the precedence of sub-project [12,13]. However, in addition to cost, due date and the precedence [14], the risk of failure of the project is also an important factor for the partner selection problem.…”

Section: Prior Workmentioning

confidence: 99%

A multi-objective optimization model of the partner selection problem in a virtual enterprise and its solution with genetic algorithms

Zhao

Hong

2005

Int J Adv Manuf Technol

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Section: Prior Workmentioning

confidence: 99%

A multi-objective optimization model of the partner selection problem in a virtual enterprise and its solution with genetic algorithms

Zhao

Hong

2005

Int J Adv Manuf Technol

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“…Various studies have explored the concept of planning in virtual enterprises or organizations (Camarinha-Matos & Afsarmanesh, 2007;Fenga & Yamashiro, 2006;Verter & Dincer, 1992;Wu, Fuh, & Nee, 2002). Nevertheless, these studies have focused on defining the objective parameters and functions of problems, which inhibits their broader application.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, these systems neglect to address potential demands and thus provide plans based on the current workload at a given time. Other studies seek to optimize the allocation of resources to maximize efficiency and minimize costs by means of different heuristic or precise optimization techniques (Fenga & Yamashiro, 2006;Verter & Dincer, 1992;Wu et al, 2002). The main problem in these cases stems from the dynamic aspect of work scenarios and the difficulty in finding a balance between time spent on planning and time spent on implementing plans, which is the key to adapting to the needs of organizations such as these that require frequent replanning.…”

Section: Introductionmentioning

confidence: 99%

Model for assigning roles automatically in egovernment virtual organizations

Zato¹,

Paz²,

Reboredo³

et al. 2012

Expert Systems with Applications

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a b s t r a c tWhen working in conjunction with multiagent systems, virtual organizations attempt to simulate the functions and interactions of entities in different environments. Recent studies have addressed the problem of assigning roles to agents that form part of the organization, and incorporating new agents to carry out certain tasks. However, these studies are limited to defining the norms and rules that determine the behavior of the organization. The present study proposes a virtual organization model for egovernment environments to assign resources and minimize the required personnel by forecasting workloads. To this end, a neural network, queuing theory, and CBR are used to obtain an efficient distribution. Queuing theory can establish the number of agents with a specific role that are necessary to maximize profits, while the network distributes roles among agents according to their respective efficiency. The final part of the paper is focused on validating the plan developed inside a case study centered on e-government in order to obtain empirical results.

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“…In order to synchronize manufacturers' production capacity with customers' demand and to coordinate the ordering of raw materials from suppliers with production schedules, a manufacturer usually orders its raw materials in small lots from suppliers and delivers its finished goods in small lots for a production system, so that both the raw materials' and finished goods' inventory is reduced [1].…”

Section: Introductionmentioning

confidence: 99%

“…Quantity of raw material i required for each batch, q b i = q/v i = n i q i t s Time between successive shipments of finished goods t Cycle time, t = q/d = mt s t 1 Manufacturing period (uptime), t 1 = q/ p x Fixed quantity of finished goods per shipment at a fixed interval of time, units/shipment, x = q/m = t s · d f( p) A function that represents unit production cost as a function of production rate…”

mentioning

confidence: 99%

Optimal production policy for a manufacturing system with volume flexibility in a supply chain under lumpy demand

Dai

Yamashiro

2004

Int J Adv Manuf Technol

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A batch production system with volume flexibility in a supply chain where a manufacturer procures raw materials and/or component parts from multiple suppliers in a lot and processes them into a single product, is considered in this research. First of all, a decision-making model is developed for an optimal production rate selection in the volume-flexibility production system, where a single type of finished products is delivered periodically in fixed quantities within a fixed interval of time. In this model, the production rate is perceived as a decision variable and unit production cost becomes a function of production rate. This model takes into account not only inventory costs of raw materials and finished goods, but production costs as well. Then, a pragmatic computation approach is presented to solve the proposed model for special unit-production-cost functions. It is used to determine an optimal production rate, and thus to decide an optimal ordering policy for procurement of raw materials from suppliers and an optimal manufacturing batch size. Some observations are made for optimal production rate analysis. Finally, a numerical study is conducted to illustrate the solution and a set of data with ten problems is tested and compared.

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A pragmatic approach for optimal selection of plant-specific process plans in a virtual enterprise

Cited by 17 publications

References 15 publications

A multi-objective optimization model of the partner selection problem in a virtual enterprise and its solution with genetic algorithms

A multi-objective optimization model of the partner selection problem in a virtual enterprise and its solution with genetic algorithms

Model for assigning roles automatically in egovernment virtual organizations

Optimal production policy for a manufacturing system with volume flexibility in a supply chain under lumpy demand

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