Revisiting Meta-Heuristic Optimization Method in solving Stochastic System Design Problem

Optimization is an important issue in the real world, and most problems can be transformed into optimization problems. However, such stochastic optimization problems are always accompanied by uncertainty, especially in the industries of innovative technologies (i.e., wearable devices and sensors on healthcare), integrated supply chain, and sustainable operations management. Due to the outbreak of COVID-19 pandemics last year, it has become quite difficult for industries to quickly obtain their supplies and optimize their operations. Therefore, a Particle Swarm Optimization Retrospective Approximation (PSORA) algorithm is proposed to solve and validate the problem using a unimodal example and sensitivity analysis. PSORA uses the framework of Retrospective approximation (RA) to iteratively solve a sequence of sample path approximation problems with increasing sample sizes;each sample path problem is solved by the improved PSO algorithm. When the sample size approaches infinite, the improved PSO algorithm solves the sample path problem to approximately identify the real objective function. Our simulation results show that PSORA is robust, and converges quickly. The result of the developed optimal model can provide marginal insights to decision-makers in problem-solving. © 2021 IEEE.

The application of Lean Six Sigma and supply chain resilience in maritime industry during the era of COVID-19

Purpose: This study aims to apply a Lean Six Sigma framework to support continuous improvement in the maritime industry (shipbuilding, logistics services and shipping companies) during COVID-19 pandemics. By applying the concepts of Lean Six Sigma and supply chain resilience, the most suitable continuous improvement method for the maritime industry is developed to maintain a resilient supply chain during COVID-19. Design/methodology/approach: A specific shipbuilding, logistics services and shipping company in Indonesia is chosen as the research object. The Lean Six Sigma framework reveals the wastes through the supply chain resilience concept, and implements internal business processes to maintain optimal system performance. Findings: The paper identifies important implementation aspects in applying Lean Six Sigma to shipbuilding, logistics services and shipping. The DMAIC (define, measure, analyze, improve and control) approach is applied to achieve supply chain resilience. Resilient measures are generated for the case companies to maximize performance during the pandemics. Practical implications: This paper provides a new insight for integrating Lean Six Sigma and resilience strategies in the maritime industry during COVID-19 disruptions. The authors provide some insights to sustain the performance of the maritime industries under study. Originality/value: This study is part of the first research in the maritime industry that focuses on continuous improvement during COVID-19 using Lean Six Sigma and supply chain resilience. © 2021, Emerald Publishing Limited.