A particle swarm algorithm for inspection optimization in serial multi-stage processes

AbstractImplementing efficient inspection policies is much important for the organizations to reduce quality related costs. In this paper, a particle swarm optimization (PSO) algorithm is proposed to determine the optimal inspection policy in serial multi-stage processes. The policy consists of three decision parameters to be optimized; i.e. the stages in which inspection occurs, tolerance of inspection, and size of sample to inspect. Total inspection cost is adopted as the performance measure of the algorithm. A numerical example is investigated in two phases, i.e. fixed sample size and sample size as a decision parameter, to ensure the practicality and validity of the proposed PSO algorithm. It is shown that PSO gives better results in comparison with two other algorithms proposed by earlier works

Understanding Adoption Intentions for Blockchain-based Personal Health Records: Integrating Technology Usage and Initial Trust Perspectives

Blockchain-based personal health records (PHR) is an impending blockchain use case that supports patient-centred care and interoperability in the healthcare industry. This paper studies the adoption of blockchain-based PHR by individuals. It proposes a multi-perspective theoretical framework containing the unified theory of acceptance and use of technology (UTAUT) and initial trust model (ITM) to understand how individuals’ perceptions and formation of trust prior to adoption may contribute to their behavioral intention toward adopting blockchain-based medical records. This research empirically tested this model using a cross-sectional questionnaire. Partial least squares structural equation modelling (PLS-SEM) was used to conduct data analysis. The results validate the theoretical model and demonstrate full support for the ITM and partial support for the UTUAT. Entrants in the blockchain-based PHR market are advised to create trustworthy systems, consider partnering with healthcare institutions to boost institution-based trust and design solutions that meet the performance expectations of users

An Integrated Location-Production-Distribution Model in the Green Supply Chain Considering Customer Service Level

Integrated production-distribution planning is one of the main issues in supply chain management that plays an important role in reducing supply chain costs. In addition, choosing optimal location of distribution centers can facilitate achieving this goal. On the other hand, environmental laws and regulations established by governments impose constraints to production and distribution activities and make necessary the adoption of green supply chain approach more than ever. In this paper, a novel model is developed for integrated location-production-distribution planning in a three-echelon green supply chain consisting of manufacturing plants, distribution centers, and customers with multiple products and multiple time periods. The objective function includes minimization of the total supply chain costs as wll as CO2 emissions throughout the chain. Also, the customer demand and service level are expressed as fuzzy Z-number in order to obtain the reliability of the values from the experts. The applicability and efficiency of the proposed model is demonstrated through a real case which, considering two indexes of customer service level and green production and distribution. In order to solve the proposed model, GAMS software package is used. Results show satisfactory performance of the proposed model in reducing costs in the green supply chain

The Impact of Business Intelligence (BI) Competence on Customer Relationship Management (CRM) Process: An Empirical Investigation of the Banking Industry

Nowadays, establishing long-term and effective relationships with customers is a key factor in understanding customers’ needs and preferences and achieving competitive advantage. In addition, companies are facing with a growing need for information and analytical knowledge about their customers, market, competitors, organizational environment, and other factors affecting their business. Business intelligence has been considered as a response to this need. The purpose of this study is to investigate the role of business intelligence competence in improving customer relationship management process. Based on the literature review and the competence – capability relationship paradigm, a conceptual model was developed comprising of different dimensions of business intelligence competence and customer relationship management processes. The data were collected from the banking sector and partial least squares structural equation modelling was employed for data analysis. Empirical results showed that organizational business intelligence competence, comprising of managerial, technical, and cultural competence, has a significantly positive impact on enhancing capabilities of customer relationship management process including initiation, maintenance, and termination of the relationship

Optimizing an integrated vendor-managed inventory system for a single-vendor two-buyer supply chain with determining weighting factor for vendor׳s ordering cost

This paper considers a two-echelon supply chain model with a single vendor and two buyers in which the vendor supplies the same item to both buyers at a finite production rate. The purpose of this study is twofold. First, mathematical models are developed for the integrated vendor-managed inventory (VMI) policy as well as the traditional retailer-managed inventory (RMI) system and solution algorithms are presented to determine the optimal lot size and total inventory cost of the supply chain. Then, the effect of key parameters including buyer[U+05F3]s demand, buyer[U+05F3]s transportation cost, vendor[U+05F3]s ordering cost, and vendor[U+05F3]s holding cost on lot size variation is studied in each policy. A weighting factor is also determined for the vendor[U+05F3]s ordering cost which is used to compare the two policies. Detailed numerical experiments are provided to illustrate efficacy of the proposed approach. Results indicate that greater reduction in total cost of supply chain can be achieved by using VMI and provide a comprehensive insight into selection of inventory policies to improve commercial business and supply chain performance

A note on the joint economic lot size model with stochastic demand and variable lead time

This paper considers the problem of choosing optimal production policy in an integrated production-inventory system comprising a single manufacturer and a single buyer. Two production scenarios are compared, namely continuous and lot-for-lot production policies, using a mathematical modelling approach and the expected total joint cost is considered as the performance measure. In addition, the lost opportunity cost due to production downtime in the lot-for-lot policy, including the cost of unemployment of human resources and stoppage of the production line, is incorporated into the model. Numerical experiment and sensitivity analysis in terms of setup and lost opportunity costs are provided to illustrate the theory and the percentage of difference in the expected total cost of the two policies is analysed. The presented approach helps managers to make the right decisions on the optimal production policy under different conditions, especially where expert and technical human resources and/or expensive production equipments are utilised

A robust-fuzzy multi-objective optimization approach for a supplier selection and order allocation problem: Improving sustainability under uncertainty

Attaining sustainability objectives has received wide attention in the supplier selection and order allocation (SSOA) literature. This paper aims to investigate an SSOA problem under multiple items, multiple suppliers, multiple price levels, and multiple period using a robust-fuzzy multi-objective programming in which: (a) transportation cost, delay penalty cost, and demand are uncertain; (b) four objectives are proposed to minimize total costs and the number of defective items and to maximize environmental and social impacts; and (c) all objectives of the problem have a fuzzy membership degree that is determined by the decision-makers. A robust optimization approach is elaborated as a solution procedure to address the uncertainty of the decision variables. The significance of each objective in practice is discussed based on seven distinct scenarios that produce a specific membership degree to help practitioners make efficient decisions in selecting the suppliers and allocating the orders. Two numerical examples with different sizes are conducted to validate the mathematical model. Thereafter, the sensitivity of each scenario on objectives and total satisfaction degree is analyzed. The results of the numerical solution compare the value of four objective functions under each developed scenario to provide a trade-off insight between different objectives for practitioners. Eventually, the credibility and efficiency of the proposed solution procedure are evaluated to validate the findings.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Rivers, Ports, Waterways and Dredging Engineerin