Under global warming, how to accurately measure and reduce ship emissions has become an important issue concerned by the transportation sector and the whole society. The diffusion concentration of continuous ship emissions is calculated by the emission concentrations at the time of observation. With the increase of observation time window, diffusion distance, and calculation accuracy, the calculation

Emergency decision making (EDM) can effectively reduce the loss caused by emergencies. The generation and selection of the alternatives are two key stages of EDM. To improve the efficiency of EDM, we propose a two stage EDM method. In the first stage, a knowledge-unit based case-based reasoning (KU-CBR) method is provided to generate alternatives. In this method, an emergency case representation model

In industrial environments, process capability indices are daily employed as numerical metrics to summarize the performance of a process according to a predefined set of specification limits. Neglecting gauge measurement errors is a common phenomenon in process capability evaluations by researchers in laboratory investigations and by practitioners in daily operations. However, this common negligence

Predictive maintenance (PdM) is a prominent anomaly prediction strategy in the manufacturing system given the increasing need to minimize downtime and economic losses. It is available for PdM to monitor industrial equipment continuously with smart electrical sensors and predict the health condition with machine learning algorithms. However, the performance of previous algorithms is often limited by

Existing feature-based transfer learning methods have achieved great performance in the transfer fault diagnosis with unlabeled data. While most of them are global alignment methods based on maximum mean difference (MMD), which ignore the differences between different faults and pay little attention to the structural information in the unlabeled target samples. This paper proposes a transfer sparse

The increase in energy demand and the effect of traditional energy generation supported by the penetration of technological advancements in renewable energy generation calls for an integrated power distribution network design. In this study, a power distribution network design with the establishment of distributed renewable energy resources and involvement of prosumers in energy system to generate

Inefficiencies in blood product management systems, including segmented operations, lack of detailed data sharing, and limited real-time visibility, can often result in significant annual losses in product wastage and postponed medical procedures. Left unaddressed, the negative impact on patient health and healthcare systems can be substantial as blood donations continue to decline. This paper proposes

The high demand for radiotherapy services, combined with the limited capacity of available resources, patient unpunctuality, and series of appointments, makes Patient Appointment Scheduling (PAS) in radiotherapy centers very challenging. Although most centers use a First-Come-First-Serve (FCFS) policy for appointment scheduling, this approach does not consider patients’ behaviors, and consequently

This paper introduces sales effort into the supply chain competition model when facing strategic customers. A comparison analysis is proposed to show the decision differences between two sales-effort modes, i.e., the supplier conducts sales effort and the retailer conducts sales effort. Supply chain members have different tendencies toward these two sales-effort modes at different wholesale prices

While a variety of disruptions are involved in the daily operation of container ports, the disruption management process in practice highly relies on the port operators’ experience or follows simple service rules. A need exists for a systematic way to adopt mathematical models to deal with these uncertainties. Considering the significance of the berth in the ports, we investigate the berth allocation

Social media plays a prominent role in the spread of mass shootings. It brought about a significant contagious effect on future similar incidents. Therefore, we explore Machine Learning (ML) models to forecast the change in the public’s attitudes about mass shootings on social media over time. These ML models include Support Vector Machine (SVM), Logistic Regression (LR), and the optimized Deep Neural

Problems of stacking items or goods occur in a plenty of applications, such as container terminals, warehouses, and steel plants. A lot of research has been done in this area in recent years. In this survey, we provide an overview of the Block Relocation Problem (BRP) and the PreMarshalling Problem (PMP) and review optimization methods for these two problems. Due to common properties between these

Prognostic and health management (PHM) effectively reduces the economic loss of sensor-equipped machine downtime caused by under-maintenance and the waste of resources resulted from over-maintenance. The remaining useful life (RUL) prediction is the most critical step in PHM. However, accurate RUL prediction in a multiple sensors data environment faces challenges and difficulties. In this paper, we

The term “Digital Twin” is used in context of a wide range of applications but neither research nor industry have agreed upon one singular definition. Presented here is a novel and formal, subject-oriented reference model for Digital Twin systems that does not focus on technical architectural concepts or particular implementation specific details, but rather on the general possibilities and functionalities

Currently, many platforms provide time-sharing rental (TSR) services to consumers by operating new energy vehicles (NEVs). We develop a two-echelon supply chain (SC) model consisting of one NEV-sharing platform (NSP) and one original equipment manufacturer (OEM) under demand uncertainty. The NSP provides TSR services and operates under two operation modes: asset-heavy mode and asset-light mode. Under

Providing warranties for healthcare is a quality and cost-effective healthcare delivery model. Under a healthcare warranty, the patient is charged a lump-sum payment for the healthcare services administered during a prespecified period regardless of the actual cost incurred by the healthcare provider. Notably, such a fixed-price healthcare delivery model increases the risks of profit maximization among

Online recycling has been recognized as an efficient method to increase the recovery amount of waste electrical and electronic equipment (WEEE). However, due to lack of supply and demand coordination, the operational performance of the “Internet + recycling” model in WEEE is not ideal. Thus, the question of how to effectively balance the relationship among consumers, recyclers, and the government is

Abstract not available

In linguistic multiple attribute decision making (MADM), flexible linguistic expressions can provide a general way to express complex preference data linguistically, which presents the challenge of handling such complex linguistic data. In this paper, we investigate the linguistic MADM with the concept of flexible linguistic expressions, and present a linguistic distribution-based approach with interval

Performance measurement is a complex but important task required in all sectors. The problem however arises when usage of different methods for performance assessment provides different results. Under such circumstances when there is a difference of opinions, rank aggregation methods can be used to provide the best solution to decision-makers (DMs). Such approaches, also known as data fusion approaches

Blockchain and the internet of things (IoT) have accelerated e-commerce growth and empowered online businesses to create value even in a globally competitive environment. The goal of this study is to develop a framework for the virtual closed-loop supply chain (VCLSC) that is based on novel blockchain and IoT technologies, as well as the concepts of sustainability and circular economy. This study integrates

In the highly competitive business environment, Supply chain (SC) disruption strongly impacted the manufacturing cost. The poor goods management and bottleneck have muddled the SC. It leads to cross-delivery, wastage of delivery time, burglary, quality and sometimes damages to the essential and precious goods. Only digitisation can be seen as an alternative to neutralise these obstacles from the procurement

This paper studies the impact of retailers’ loyalty programs (LPs) in a supply chain context. We consider a supply chain formed by one manufacturer selling its product through two competing retailers and focus on frequency loyalty programs that reward consumers with a free product after several purchases. Two different games are modeled: (1) a Stackelberg game, where the manufacturer is the leader

Online robust parameter design (RPD) for the complex production process has recently attracted increasing attention among researchers and practitioners. However, the existing online RPD methods usually ignore the model uncertainty of initial steps, which may lead to the overestimated optimal solutions in the early stage of online RPD. This paper proposes a multi-stage robust optimization approach based

In this study, we consider a stochastic joint replenishment problem with Poisson demand, where multiple items are replenished jointly through a common supplier. We study a novel type of joint replenishment policy controlled by a sales threshold, under which new orders are placed to restore every item’s inventory position to a base-stock level when the system’s accumulated sales generated since the

Railway organizations are spending on digitizing rail freight transportation for better resource utilization and revenue generation. In 2010, the Indian Railway (IR) proposed a “Special Freight Train Operator” scheme to build an IR stake in freight transportation in high-capacity rakes. IR allowed freight train operators (FTOs) and manufacturers to invest in wagons and take benefit of the largest rail

Remanufactured products belong to the category of environmentally friendly products. Here, we develop models and strategies for collaborating and co-branding of luxury brands with other companies for producing remanufactured products of luxury brands. Then, we examine whether the strategies can coordinate them for producing remanufactured products or not, because of small market share of luxury brands

In this paper, the bullwhip effect is analytically measured for a two-stage supply chain, including a manufacturer, and a retailer who serves a market demand. The demand is assumed to be a combination of a first-order autoregressive process, a retail price (set by the retailer), and an asymmetric customer reference price (representing the customer valuation). Furthermore, a series of existence conditions

Against the background of a low-carbon economy and the rising environmental awareness, extensive attention has been paid to carbon emissions in the cold chain in academic research and practice. In cold chain operations, consumers’ preference for freshness is also growing, which motivates the investment in preservation technology to improve the freshness of perishable products. However, further investment

The upcoming industrial revolution 4.0 built on the internet of things, and prescriptive analytics paves the way for the spread of continuously monitored condition-based maintenance (CBM) in the industry. In the CBM implementations, it is essential to consider the impact of spare parts quality, lead-time, and inspection errors on maintenance cost and system availability. We propose a new maintenance

In this paper selection of fast algorithm portfolios for 2SP packing problem is considered. The 2SP problem consists in placing rectangles on a strip of the given width for minimum strip length. The 2SP packing has application in many industries, but suitability of the related algorithms is limited by their runtimes. While solving combinatorial optimization problems, longer runtimes increase chances

The manuscript addresses the copula-based CUSUM charting scheme to monitor infectious disease. To facilitate the disease surveillance, the Poisson distribution is often used to model the number of diseases counts while the Markov process is used to model the serial correlation within sequential observations. In literature, the first-order autoregressive (AR(1)) process and the first-order integer autoregressive

In the context of integrated energy substitution and retail side liberalization, we develop a novel alternative energy trading mechanism in the presence of price competition and value-added service to study the purchase and sale strategies for integrated energy retailers. Under the mechanism, the retailer first joins a second-price sealed auction to make an optimal electricity purchase. If the retailer’s

With the development of international trade, the core position of port transportation progressively emerges. However, most current port supply chain systems adopt a centralized data management mode. Each operator in the supply chain has its platform and data set, which is prone to form information islands and can create trust issues, resulting in the inefficient overall operation of the supply chain

Social network group decision-making (SNGDM) has become popular recently in the area of decision analysis as the social network can effectively model the relationship among decision makers. In the SNGDM, decision makers will present conflicting assessments due to individual differences in education backgrounds and cognitive levels. This study aims to develop a personalized consensus reaching framework

For enhancing the charging infrastructure network coverage in populated areas, photovoltaic pavement (PVP) has been considered an innovative option that caters to distributed power generation and electric vehicles (EVs) charging in motion. However, the promotion of PVP has not yet served its intended purpose. This paper develops a gross net present value (GNPV) model to investigate the optimal timing

The development of omni-channel retailing brings both opportunities and challenges to conventional supermarkets. Utilising local establishments to complete online customer orders is critical to providing timely and seamless omni-channel shopping experiences. We propose a bi-objective mixed-integer non-linear order batching and assignment optimisation model with the objectives of minimising person-hours

The companies producing durable products consider various strategies to attract customers’ attention and maximize their profit. The two inseparable policies utilized by these companies are free-replacement warranty and Trade-in. Both policies profoundly impact customers’ buying behavior and producers’ profit. In this article, we investigate a monopolist manufacturer producing durable products over

One of the most destructive effects of pandemics and epidemics outbreak is the severe deficiency of basic goods needed by society, especially in underdeveloped and developing countries. Therefore, designing an efficient managerial model for making operative modifications in logistics networks beside the governmental financial support policies is considered as one of the most important managerial challenges

Additive manufacturing (AM) is a revolutionary technological advancement that has the potential to contribute to sustainability in operations. The environmental benefits offered by AM have motivated firms to the adoption of this technology. However, the real-world examples of successful applications of AM are limited. This study aims to explore and prioritise the challenges faced during the adoption

In this paper, a multi-objective integrated production and energy model for sustainable supply chain design, planning, and energy source selection has been proposed. The model considers economic, environmental, and social concerns. The lexicographic procedure was applied to compromise the conflict objectives with different percentages of deviations. It aims to maximize both profit and overall customer

With the development of society and technology, the modern manufacturing system is required to handle unpredictable and rapidly changing market demands during various demand periods. This is a new challenge to the production scheduling of the production line, which requires a faster and smarter response to changes in production demand. To meet the challenge, the reconfigurable manufacturing system

With the increasing development of artificial intelligence (AI) technologies, deep learning-driven approaches have been widely applied to predicate different machinery failures. One key challenge of failure prediction is to collect sufficient data, especially data of various failure types, to train the data-driven models. Existing studies focus on using transfer learning to transfer knowledge across

We consider a two-stage supply chain consisted of one supplier and two retailers in a two-period selling, where retailers compete for limited capacity, and the supplier adopts both a minimum order quantity contract and allocation mechanisms during dealing with retailers. In this study, we solve the equilibrium order quantities of retailers in the presence of the minimum order quantity under fixed and

In recent years, the government and consumers are concerned about environmental issues. Motivated by carbon regulations and consumers’ low-carbon preferences, manufacturers have implemented carbon emission reduction (CER) through green technologies and remanufacturing. Most of the existing literature related to the low-carbon supply chain considered single carbon regulation and assumed that enterprises

To underpin a reverse logistics (RL) outsourcing decision, this study aims to investigate a third-party reverse logistics provider (3PRLP) selection problem under the framework of group decision making (GDM). Group attitude towards distinctive opinions may affect the time and cost on consensus reaching process (CRP). Therefore, an attitudinal consensus method under uncertainty is established and composed

The Crew Scheduling Problem (CSP) is an important and difficult problem in railway crew management. In this paper, we focus on the railway crew scheduling problem with time window constraints caused by meal break rules. To address these complex crew scheduling rules, we construct a Time-Space-State Network (TSSN), formulate the studied problem as an initial network flow model and a strengthened network

At present, there are mainly two service modes in the field of industrial service, referring to field service and factory service, in which all the service processes occur in user-specified places and the factory workshops, respectively. Their compulsive constraints on the service sites inevitably result in the limited service areas, high service costs, and long service cycles. However, with the market

Environmental, social and governance (ESG) issues arouse wide concern in both industry and academia to promote sustainable development. Listed companies assume the responsibility to submit annual reports to disclose their ESG outcomes genuinely. However, the challenge is that companies may overstate or slur their actual sustainable performance, and the entire ESG reporting process is hidden backward

This study addresses the problem of resilient mixed open and closed-loop supply chain network design under operational and disruption risks as a fundamental domain in supply chain management. To deal with disruption risks, several resilience strategies (including multiple sourcing, facility fortification, adding extra production capacity, multi-channel distribution, and pricing) are applied. A model

In recent years, artificial intelligence has been applied in the industry to automate various vision-based applications, such as monitoring structural defects in manufactured products. For industrial inspections, the automatic detection and localization of defective parts from product images ensure quality while avoiding waste of labor and materials. To this end, this paper introduces a two-branch

To achieve better environmental performance and lessen waste, governments are setting mandatory take-back legislation that requires manufacturers to recycle and remanufacture waste products (i.e., remanufactured products) as much as possible. In this background, enterprises with long-term vision proactively introduce charitable donations into remanufactured products to realize both environmental and

This paper presents constraint programming-based solution approaches for the three-dimensional loading capacitated vehicle routing problem (3L-CVRP) that consists of vehicle routing and three-dimensional loading problems in distribution logistics. Despite the practical benefits in the logistics world, the 3L-CVRP has not been extensively studied in the literature for its high combinatorial complexity

The innovative enterprise entering a new market makes optimal decisions based on consumer behavior and market conditions. This study investigates product pricing strategy and quality strategy by considering the brand goodwill of the innovative enterprise and the consumers’ quality expectation. We mainly analyze three scenarios including the innovative product strategies with no competition, competitive

Automation of traffic light control (TLC) systems is the major focus area compliant with Industry 4.0. The majority of the adaptive TLC systems are designed for homogeneous traffic of four-wheeler vehicles and are responsive to the prevailing traffic conditions at a junction. Further, they do not serve priority vehicles such as public transport (buses) or emergency vehicles (ambulance, fire trucks

Strengthening the use of preventive services in primary care has become the key to solving the problem of a global increase in healthcare expenditures caused by aging populations and chronic diseases. In practice, whether devoting effort to preventive services can be a strategic decision when the limited working time keeps a general practitioner (GP) busy with diagnosis and treatment. Based on the

Increasing pressure from customer expectations to government regulation for sustainable food products warrants research in the sustainable food supply chain (FSC). One-third of the food produced is wasted, despite the potential to valorize food wastes. Additionally, the uncertainty associated with the supply of food products has a significant impact on the FSC decisions, steering the need for robust

Due to technological advances, Big Data Analytics (BDA) has become increasingly important over the last few years. This has led companies to evolve BDA capabilities (BDAC) to manage operations and make better decisions. In this study, we propose a model, Clustering Based Classifier Ensemble Method for Cost of Defect Prediction (CBCEM-CoD), incorporating clustering, classification, prediction, and learning

The latest research in the field of casual relations using fuzzy cognitive maps utilizes various adaptive supervised learning techniques. These supervised methods provide promising data understanding and processing the fuzzy outcomes. This article contributes in the modern research by providing an adaptive review of different knowledge-oriented methods for the establishment of Fuzzy Cognitive Maps