A trade-off multiobjective dynamic programming procedure and its application to project portfolio selection

A methodology for strategy-oriented project portfolio selection taking dynamic synergy into considerations

“…As described earlier in Section 1, current researches and developments usually consider projects in the portfolio are individually, which ignore that single project selection criterion may conflict with strategy of the organization. Nowak & Trzaskalik [37] proposed a trade-offs approach and developed assessment criteria, which can be used to evaluate the project selection process over a specified period to solve a stochastic discrete project portfolio selection problem. However, such an approach ignores that the dynamically synergetic relationships among candidate projects have a major impact on the selection of projects that needs to be taken into consideration to satisfy the company's strategy.…”

Integration of production scheduling and energy-cost optimization using Mean Value Cross Decomposition

“…Yet, interest in dynamic multiobjective problems has been increasing and new approaches have been suggested based on, e.g., genetic algorithms (Raquel et al 2013) and evolutionary techniques (Deb et al 2007, Helbig and Engelbrecht 2014, and Orouskhani et al 2019. New interactive approaches have also been developed by focusing on only part of the possible Pareto solutions directly by using the decision maker's preference knowledge (Nowak andTrzaskalik 2021, andAghaei Pour et al 2021). For a recent extensive survey on dynamic multiobjective optimization, see Jiang et al (2022).…”

Selection of Appropriate Portfolio Optimization Strategy

“…To achieve this objective, numerous optimization algorithms have been proposed and employed in the field [1]. Among these algorithms, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and DP have emerged as commonly utilized approaches for portfolio optimization [2][3][4][5][6][7][8][9]. However, in recent years, the Differential Evolutionary Algorithm (DE algo) has garnered significant attention and popularity due to its effectiveness in tackling diverse optimization problems, including those within the domain of finance [10].…”