Multi-objective optimization based on the utopian point method applied to a case study of osmotic dehydration of plums and its storage

Szparaga, Agnieszka; Stachnik, Marta; Czerwińska, Ewa; Kocira, Sławomir; Dymkowska-Malesa, Maria; Jakubowski, Marek

doi:10.1016/j.jfoodeng.2018.10.014

Cited by 18 publications

(13 citation statements)

References 18 publications

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“…The independent variables for optimizations included window-to-wall ratio and algae concentration. In this research, the first method for the optimization process includes simulating design solutions and investigating Pareto optimum solutions by using the Utopian point method applied for multi-objective optimization [63,64], while the second method was conducted based on an evolutionary algorithm to evaluate the first process and enhance the methodology.…”

Section: Methodsmentioning

confidence: 99%

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Talaei

Mahdavinejad

Azari

et al. 2021

Journal of Building Engineering

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Section: Methodsmentioning

confidence: 99%

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Talaei

Mahdavinejad

Azari

et al. 2021

Journal of Building Engineering

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“…However, those multi-objective goals are sometimes not coordinated or even contradictory. Multi-objective optimization is thereby a complex mathematical process that aims to find a best trade-off for a given problem by satisfying all constraints [9].As a consequence, multi-objective planning has increasingly gained research attention:…”

Section: Related Work a Multi-objective Optimizationmentioning

confidence: 99%

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

Zhao

Gui

et al. 2020

IEEE Access

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In order to improve the performance and change the current situation of the cost minimization model widely used in the cold chain logistics distribution process, a multi-objective optimization model based on cost, carbon emissions and customer satisfaction is proposed. Considering the characteristic of this proposed optimization model, we design an improved ant colony algorithm with a multi-objective heuristic function to solve it, termed as ACOMO. Experimental results show that the proposed ACOMO can effectively solve the vehicle routing problem of the multi-objective optimization model, and outperforms the classic ant colony algorithms, resulting in more Pareto optimal solutions. It offers an environmentally friendly distribution solution for the problem. Specifically, the distribution path obtained by the improved ant colony algorithm manages to achieve the above multiple goals, including reduction of distribution costs and carbon emissions, and improvement of customer satisfaction. In addition, compared with a single-target model that only provides one single distribution route to cost minimization, multi-objective optimization can provide a variety of distribution route options for logistics companies in practice. Finally, through the sensitivity analysis of temperature changes and cargo damage coefficients, the proposed system successfully provides reference for the optimization of the path of cold chain logistics enterprises, and promotes logistics enterprises to effectively arrange their work and to be more socially responsible. INDEX TERMS Cold chain logistics, path optimization, multi-objective optimization, carbon constraints, customer satisfaction.

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“…The moisture content of foods was linked to the loss of water by diffusion through the skin and by evaporation from the tissues in the fruits (Garcia et al, 2014). OD tends to reduce the moisture content of samples involved (Szparaga et al, 2019) by 30% to 70% (Raoult-Wack et al, 1991). A study conducted by Sulaeman et al (2004) also revealed that the moisture content of their carrot chips varied from 1.96% to 2.68% according to the treatments used.…”

Section: Total Moisture Contentmentioning

confidence: 99%

TEXTURE ANALYSIS OF STARFRUIT (Averrhoa carambola) CHIPS PRE-TREATED WITH GLUCOSE SYRUP AND OSMOTIC DEHYDRATION

Omar

Razak

Ramly

2020

MABJ

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Osmotic dehydration (OD) of starfruit chips by glucose syrup was chosen as the osmotic agent (OA) in this study as it is believed to confer a desirable result in the final product. As in this study, the concentration of glucose syrup that was used is 30, 40 and 50°Brix with soaking temperature of 20°C to 60°C and soaking time of 20 min to 60 min. The result showed that higher water loss and lower solid gain of starfruits obtained as the higher temperature and glucose syrup concentrations were used. Meanwhile, processing of osmo-dried starfruits into chips were done by stir frying with canola oil. The use of glucose syrup with concentration of 50°B, 60°C temperature and 60 min soaking time produced the highest hardness and crispness of starfruit chips with the lowest moisture content. Test of significance (p<0.05) in results obtained from this study were determined using Minitab 18 software as one-way Analysis of Variance (ANOVA) and Tukey-Test. In general, OD pre- treatment could be proved as an effective technique for food industries to develop fried starfruit chips with improved texture quality.

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Multi-objective optimization based on the utopian point method applied to a case study of osmotic dehydration of plums and its storage

Cited by 18 publications

References 18 publications

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Multi-objective optimization of building-integrated microalgae photobioreactors for energy and daylighting performance

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

TEXTURE ANALYSIS OF STARFRUIT (Averrhoa carambola) CHIPS PRE-TREATED WITH GLUCOSE SYRUP AND OSMOTIC DEHYDRATION

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