Fuzzy R&amp;D portfolio selection of interdependent projects

Due to the increasing size of the population, society faces several challenges for sustainable and adequate agricultural production, quality, distribution, and food safety in the strategic project portfolio selection (SPPS). The initial adaptation of strategic portfolio management of genetically modified (GM) Agro by-products (Ab-Ps) is a huge challenge in terms of processing the agro food product supply-chain practices in an environmentally nonthreatening way. As a solution to the challenges, the socio-economic characteristics for SPPS of GM food purchasing scenarios are studied. Evaluation and selection of the GM agro portfolio management are the dynamic issues due to physical and immaterial criteria involving a hybrid multiple criteria decision making (MCDM) approach, combining modified grey Decision-Making Trial and Evaluation Laboratory (DEMATEL), Multi-Attributive Border Approximation area Comparison (MABAC) and sensitivity analysis. Evaluation criteria are grouped into social, differential and beneficial clusters, and the modified DEMATEL procedure is used to derive the criteria weights. The MABAC method is applied to rank the strategic project portfolios according to the aggregated preferences of decision makers (DMs). The usefulness of the proposed research framework is validated with a case study. The GM by-products are found to be the best portfolio. Moreover, this framework can unify the policies of agro technological improvement, corporate social responsibility (CSR) and agro export promotion.

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“…Bhattacharyya et al [40] Multiple objective GA Fuzzy R&D portfolio selection of interdependent projects.…”

Section: Jiang Et Al [39] Ahpmentioning

confidence: 99%

A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

Debnath¹,

Roy

Kar

et al. 2017

Sustainability

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“…Once these objectives are identified, the most suitable portfolio can be identified and eventually adjusted on a more dynamic basis -reflecting the acceleration of scientific progress and the convergence of traditionally separate fields. Interesting methods already under development [Van Bekkum, Pennings, 2009;Zapata, Reklaitis, 2010;Bhattacharyya, 2011] can become first-rate decision-making tools that prevent non-expert policy makers and managers from making simplistic statements justifying or rejecting research on the basis of emotional (rather than rational) appeal.…”

Section: Dynamic Methods •mentioning

confidence: 99%

From Research Project to Research Portfolio: Meeting Scale and Complexity

Linton

Vonortas

2015

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Keywordsresearch and development (R&D); peer review of R&D projects; project portfolio; portfolio-based approach; research performance evaluation From Research Project to Research Portfolio: Meeting Scale and ComplexityInvestment in research and innovation faces increasing scrutiny in countries that already do a lot of it. How much investment is optimal? How can we tell if and when our research activities offer less value for the dollar spent on them? How can we ensure that the benefits of investments accrue to those who incur the cost?

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“…Recently, PPS has become one of the most active research topics in the fields of economic analysis (e.g., see Tofighian and Naderi 2015;Lee et al 2006;Wu and Chen 2015), R&D projects (e.g., see Fang et al 2008;Bhattacharyya et al 2011;Hassanzadeh et al 2014), supplier selection (e.g., see Hosseininasab and Ahmadi 2015;Vazhayil and Balasubramanian 2014;Lorca and Prina 2014), etc. Any model to solve this problem should consider relations between projects, uncertainties associated with incomes and risk issues so that the obtained results to be more valid.…”

Section: Introductionmentioning

confidence: 99%

Multi-period project portfolio selection under risk considerations and stochastic income

et al. 2018

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This paper deals with multi-period project portfolio selection problem. In this problem, the available budget is invested on the best portfolio of projects in each period such that the net profit is maximized. We also consider more realistic assumptions to cover wider range of applications than those reported in previous studies. A novel mathematical model is presented to solve the problem, considering risks, stochastic incomes, and possibility of investing extra budget in each time period. Due to the complexity of the problem, an effective meta-heuristic method hybridized with a local search procedure is presented to solve the problem. The algorithm is based on genetic algorithm (GA), which is a prominent method to solve this type of problems. The GA is enhanced by a new solution representation and well selected operators. It also is hybridized with a local search mechanism to gain better solution in shorter time. The performance of the proposed algorithm is then compared with well-known algorithms, like basic genetic algorithm (GA), particle swarm optimization (PSO), and electromagnetism-like algorithm (EM-like) by means of some prominent indicators. The computation results show the superiority of the proposed algorithm in terms of accuracy, robustness and computation time. At last, the proposed algorithm is wisely combined with PSO to improve the computing time considerably.

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Fuzzy R&D portfolio selection of interdependent projects

Cited by 94 publications

References 23 publications

A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

A Hybrid MCDM Approach for Strategic Project Portfolio Selection of Agro By-Products

From Research Project to Research Portfolio: Meeting Scale and Complexity

Multi-period project portfolio selection under risk considerations and stochastic income

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