A new ABC-based multiobjective optimization algorithm with an improvement approach (IBMO: improved bee colony algorithm for multiobjective optimization)

Sağ, Tahir; Çunkaş, Mehmet

doi:10.3906/elk-1402-310

Cited by 5 publications

(1 citation statement)

References 40 publications

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“…All these algorithms have been tuned to be tested on a known test function. Thus, an artificially constructed test function named ZTD1 [E. Zitzler et al, 2000] is adopted as it allows easy implementation, easy visualization and known optima in advance [T. Sağ et al, 2016]. ZTD1 has a convex Pareto optimal front, n = 30 with x_i#[0, 1] and its objective functions are:…”

Section: Statement Of Theory and Definitionsmentioning

confidence: 99%

A Hydrocarbon Production System Multi-Objective Optimization

Cascio

Maio

Bianco

et al. 2020

Day 3 Wed, January 15, 2020

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The benefits of a multi-objective optimization approach embedding an accurate exergy model of a hydrocarbon production system are shown on a real oil and gas facility. The innovative tool developed is based on a biogenetical differential evolution algorithm, which exploits a self-adaptive iterative procedure to maximize the value of the Asset. The optimization integrates the production system considering the trade-off between hydrocarbon production, energy consumption and efficiency. The Asset value optimization is one of the most complex and multi-disciplinary task in the oil and gas industry, due to the high number of objectives and their synergy. An integrated physical model of wells, gathering network and process plant is built and, then, used for exergy efficiency and gas production optimization. Conflicts and interactions among process variables and operational constraints are treated and solved holistically by the tailored evolutionary algorithm. This has also been integrated with a quick and efficient exergetic and thermoeconomic analysis in order to grant the achievement of the maximum asset value. The multi-objective optimization provides a trade-off between the optimal values of exergy efficiency and gas production that would have been obtained independently with single-objective optimizations. In fact, the exergy efficiency optimization is driven towards a configuration having lower irreversibilities: by apportioning the entire system exergy into the exergy destroyed by each piece of equipment and by calculating its local efficiency, the most contributing to irreversibility generation is identified. Moreover, the exergy analysis is complemented with an exergetic and a thermoeconomic cost analysis: the exergy analysis, apart from describing the quality of any thermodynamic process, does not give any information about the costs of each system stream, which can be even more interesting and of practical application. Indeed, the exergy analysis is proven to be an accurate way of assessing which equipment is performing worse. Therefore, it leads to preventive corrective actions to ensure good thermodynamic performance of the system and supports the decision process in the choice of maintenance operations. The thermoeconomic analysis, based on the theory of exergetic costs, confirms the improved management of the process plant and its efficiency enhancement, without neglecting the main target of the oil and gas industries that is production maximization. The benefits of a novel multi-objective biogenetical approach to solve and optimize a hydrocarbon production system in terms of exergy efficiency and gas production are shown, with respect not only to other methodologies of literature but also in terms of exergetic and thermoeconomic costs of the solutions provided, allowing to achieve the highest value of the operated asset.

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Section: Statement Of Theory and Definitionsmentioning

confidence: 99%