Multicriteria decision making applied to waste recycling: comparison between THOR and THOR 2 methods

Souza, Letícia de Oliveira Gago Ramos de; Vitorino, Lucas; Gomes, Carlos Francisco Simões; Quelhas, Osvaldo Luiz Gonçalves

doi:10.1590/0103-6513.20220128

Brasil

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Research Article • Prod. 33 • 2023 • https://doi.org/10.1590/0103-6513.20220128 linkcopy

Multicriteria decision making applied to waste recycling: comparison between THOR and THOR 2 methods

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Paper aims This paper aims to compare the results of the THOR2 Method, in comparison to the original THOR method, and to analyse possible rank changes between the methods, to support decision-making in the evolutionary process of waste recycling in Brazil.

Originality ; Proposes a revision of the model for analysis of Waste Recycling, highlighting the vision of three decision makers individually, and later the integrated vision.

Research method State of the art of the THOR and THOR2 methods, through an investigation in four databases and comparison using THORWeb.

Main findings As a result of the disposal of plastic waste, reuse, mechanical recycling, chemical and incineration remained in the positions with the consumer as a decision maker. With the other decision makers there was only one significant change, where the landfill went from last to first position.

Implications for theory and practice There was only one significant change when comparing methods.

Keywords Waste; Multicriteria; Sustainability; THOR method

Title	Authors and year	Journal	Citation	Data base
Strategy Analysis for project portfolio evaluation in a technology consulting company by the hybrid method THOR	Santos et al. (2022)	Procedia Computer Science, v. 199, p. 134-141, 2022.	1	Scopus
Demand Prioritization on Supply Chain by the Integration of Value-Focused Thinking Approach and THOR 2 Method	Esteves et al. (2022)	Procedia Computer Science, v. 214, p. 248-256, 2022.	1	Scopus
A fuzzy scale approach to the THOR algorithm	Elacoste et al. (2022)	Pesquisa Operacional 42: e261547 p.1-25	0	Scielo Brazil
THOR 2 Method: An Efficient Instrument in Situations Where There Is Uncertainty or Lack of Data	Tenório et al. (2021)	IEEE Access 9, pp. 161794-161805	2	Scopus and Web of Science
Ballast water management: technology choice comparing TODIM and THOR 2	Gomes et al. (2021)	Independent Journal of Management & Production 12 (8), pp.2140-2160	1	Web of Science
Navy Warship Selection and Multicriteria Analysis: The THOR Method Supporting Decision Making	Tenório et al. (2020)	Springer Proceedings in Mathematics and Statistics 337, pp. 27-39	17	Scopus
Choosing a hospital assistance ship to fight the covid-19 pandemic	Costa et al. (2020)	Revista de Saúde Pública 2020;54-79	20	Scielo Brazil
Application of multicriteria methods to the problem of choice models of electronic payment by credit card	Gomes & Costa (2013)	Production v. 25, n. 1, p. 54-68	12	Scielo Brazil
Using multicriteria decision support in a biomass alternatives ordination problem	Gomes & Maia (2013)	Production v. 25, n. 1, p. 54-69	2	Scielo Brazil
Decision analysis for the exploration of gas reserves: merging Todim and Thor	Gomes et al. (2010)	Pesquisa Operacional v.30, n.3, p.601-617	20	Scielo Brazil
Uso de SAD no apoio à decisão na destinação de resíduos plásticos e gestão de materiais	Cardoso et al. (2009)	Pesquisa Operacional v.29, n.1, p.67-95	27	Scielo Brazil
Multicriteria decision making applied to waste recycling in Brazil	Gomes et al. (2008)	Omega Volume 36, Issue 3, June 2008, Pages 395-404	83	SciencDirect
Modelagem analítica aplicada à negociação e decisão em grupo	Gomes (2006)	Pesquisa Operacional v.26, n.3, p.537-566	2	Scielo Brazil
Using MCDA methods THOR in an application for outranking the ballast water management options	Gomes (2005)	Pesquisa Operacional v.25, n.1, p.11-28	22	Scielo Brazil

	Criteria
	Investments (euros/kg d)	Operational costs (euros/kg)	Disposal/treatment costs (euros/kg)	CO₂ emissions (kg/kg)	Corporate image	Benefits (euros/kg)
Criteria weights
Government	4	1	3	5	2	6
Manager	3	5	4	1	2	6
Consumer	3	1	2	4	6	5
Integrated	3	2	3	3	3	5

Alternatives
p	4	0.02	0	0.02	0	0
q	2	0.01	0	0.01	0	0
Veto	300	0.4	0.2	3.2	10	0.3
Reuse	-5	−0.2625	−0.00561	−0.062	11	+ 0.181
Landfill	−0.038	−0.1810	0	−0.014	3	0
Thermal recycling	-254	−0.1701	−0.00360	−3.116	7	+ 0.014
Chemical recycling	-454	−0.2977	−0.00228	−0.533	5	+ 0.255
Mechanical recycling	-10	−0.2917	−0.00623	−0.069	9	+ 0.280
Incineration	-231	−0.1547	−0.00327	−2.833	1	+ 0.181

	Operation time (years)	Installed capacity (ton/h)	Present production (ton/d)	Initial investment cost (10³ US$)	Present status
Weight	1	1	1.2	1.2	1.2
Membership function	1	1	1	1	1
Facilities
p	0.5	2	4	3	0.4
q	0.2	1	2	2	0.2
Veto	9	93	200	200	5
A	7	100	230	1000	Stopped
B	6	30	80	210	Stopped
C	1	40	60	83	Stopped
D	1	20	170	159	Operating
E	3	10	10	36	Operating
F	1	25	30	100	Operating
G	0.3	15	45	67	Operating
H	9	40	210	150	Operating
I	8	40	210	183	Operating
J	7	15	80	109	Stopped
K	3	30	100	80	Operating
L	0.5	30	1	85	Stopped
M	4	35	32	115	Operating

Alternative	Consumer	Government	Organization	Integrated
*S1 Score*
Reuse	3.38	2.98	2.79	2.97
Mechanical recycling	3.24	3.5	2.24	2.79
Chemical recycling	2.00	2.0	1.67	1.90
Thermal recycling	0.67	0.57	0.53	0.58
Incineration	0.67	1.38	1.84	1.77
Landfill	0.57	0	0	0
*S2 Score*
Reuse	3.38	2.98	2.79	2.97
Mechanical recycling	3.24	3.5	2.24	2.79
Chemical recycling	2.00	2.0	1.67	1.89
Thermal recycling	0.71	0.62	0.76	0.68
Incineration	1.21	1.43	2.07	1.87
Landfill	0.5	0	0	0
*S3 Score*
Reuse	3.81	3.48	2.83	3.37
Mechanical recycling	3.29	3.57	2.48	2.89
Chemical recycling	2.00	2.0	1.67	1.89
Thermal recycling	0.71	0.62	0.76	0.68
Incineration	1.21	1.43	2.07	1.89
Landfill	0.5	0	0	0

Alternative	Consumer	Government	Organization	Integrated
S1 Score
Reuse	3.374	2.494	2.263	2.458
Mechanical recycling	3.119	2.429	1.773	2.232
Chemical recycling	1.839	1.439	1.153	1.324
Thermal recycling	0.55	0.0	0.5	0.5
Incineration	0.665	0.862	1.733	0.749
Landfill	1.207	3.043	2.339	2.826
S2 Score
Reuse	3.374	2.494	2.263	2.458
Mechanical recycling	3.119	2.429	1.773	2.232
Chemical recycling	1.839	1.439	1.153	1.324
Thermal recycling	0.577	0.0	0.582	0.516
Incineration	0.703	0.9	1.93	0.834
Landfill	1.207	3.043	1.839	2.326
S3 Score
Reuse	3.613	2.796	2.285	2.695
Mechanical recycling	3.144	2.455	1.91	2.289
Chemical recycling	1.839	1.439	1.153	1.324
Thermal recycling	0.577	0.0	0.582	0.516
Incineration	0.703	0.9	1.93	0.834
Landfill	1.207	3.043	1.839	2.326

Facilities	S₁	S₂	S₃	S₄ “no weights”
K	8.57	8.57	11.57	11.40
I	8.43	8.43	11.29	11.00
H	8.43	8.43	11.14	11.00
D	6.64	6.64	7.57	7.00
M	5.71	5.71	7.14	6.40
E	5.57	5.57	6.14	5.20
C	3.71	3.71	4.57	4.40
B	3.36	3.36	4.57	4.40
G	3.14	3.14	4.00	3.60
F	3.14	3.14	4.00	3.40
J	3.07	3.07	3.86	3.00
L	2.00	2.00	2.86	2.60
A	1.50	1.50	1.71	2.40

Facilities	S1	S2	S3
K	5.157	5.157	5.828
I	9.468	9.468	10.53
H	9.228	9.228	10.238
D	5.263	5.441	6.224
M	5.601	5.601	6.254
E	0.607	0.607	0.607
C	2.393	2.62	2.922
B	5.972	5.972	6.638
G	1.18	1.18	1.369
F	2.463	2.641	2.95
J	3.92	3.92	3.758
L	1.0	0.5	0.529
A	9.326	9.326	9.93

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[1] Source: Gomes et al. (2008).