Balancing timeliness and sustainability in new product development: a simulation-based multi-objective optimization approach

Purpose This study aims to develop a simulation-based optimization framework to manage the strategic dual-objective conflict in new product development (NPD). The proposed model simultaneously seeks a Pareto-optimal balance between two conflicting goals: minimizing Total Weighted Project Tardiness (Z1) and maximizing the Project Green Development Score (Z2). Design/methodology/approach The model relies on a Stochastic Job Shop structure simulated in the Arena environment. To accurately weigh sustainability criteria, the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) was used, incorporating a critical new measure: policy compliance. The performance of seven priority rules was evaluated within a multi-objective optimization framework to derive the Pareto Front. Findings Results confirm a distinct Pareto Trade-off curve between Z1 and Z2. Priority rules were classified into three strategic regions: Timeliness-Focused (SPT), Sustainability-Focused (GP) and Intelligent Balanced (EDD, CR). Analysis reveals that achieving a higher sustainability score incurs a quantitative cost: an increase of 217.4 units in weighted tardiness. Originality/value To the best of the authors’ knowledge, this study is among the first to integrate Fuzzy AHP for sustainability weighting within a stochastic R&D scheduling environment. It contributes to the literature by providing a quantitative “Strategic Classification” of priority rules, moving beyond single-objective optimization to offer a decision-making portfolio for managers facing environmental mandates.

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Publication Details

Journal
Journal of Science and Technology Policy Management
Published
2026-08-03
DOI
https://doi.org/10.1108/jstpm-01-2024-0012
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
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article

Balancing timeliness and sustainability in new product development: a simulation-based multi-objective optimization approach

Sadegh Shahbazi, Seyed Mohammad Masoud Naserian, Hosein Vahidy
Journal of Science and Technology Policy Management
Sustainable Supply Chain Management
article

Balancing timeliness and sustainability in new product development: a simulation-based multi-objective optimization approach

Sadegh Shahbazi, Seyed Mohammad Masoud Naserian, Hosein Vahidy
article en

Abstract

Purpose This study aims to develop a simulation-based optimization framework to manage the strategic dual-objective conflict in new product development (NPD). The proposed model simultaneously seeks a Pareto-optimal balance between two conflicting goals: minimizing Total Weighted Project Tardiness (Z1) and maximizing the Project Green Development Score (Z2). Design/methodology/approach The model relies on a Stochastic Job Shop structure simulated in the Arena environment. To accurately weigh sustainability criteria, the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) was used, incorporating a critical new measure: policy compliance. The performance of seven priority rules was evaluated within a multi-objective optimization framework to derive the Pareto Front. Findings Results confirm a distinct Pareto Trade-off curve between Z1 and Z2. Priority rules were classified into three strategic regions: Timeliness-Focused (SPT), Sustainability-Focused (GP) and Intelligent Balanced (EDD, CR). Analysis reveals that achieving a higher sustainability score incurs a quantitative cost: an increase of 217.4 units in weighted tardiness. Originality/value To the best of the authors’ knowledge, this study is among the first to integrate Fuzzy AHP for sustainability weighting within a stochastic R&D scheduling environment. It contributes to the literature by providing a quantitative “Strategic Classification” of priority rules, moving beyond single-objective optimization to offer a decision-making portfolio for managers facing environmental mandates.

Journal of Science and Technology Policy Management
Malek Ashtar University of Technology (IR)
Openalex Percentile: Top 7%
Sustainable Supply Chain Management
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