Managing disruptions in the maritime industry – a systematic literature review

PurposeThis paper presents a systematic review of the literature in the domain of maritime disruption management, upon which future research framework and agenda are proposed. Two review questions, i.e. the measures that are employed to manage disruptions and how these contribute to resilience performance, were pursued.Design/methodology/approachThe systematic literature review procedure was strictly followed, including identification and planning, execution, selection, and synthesis and analysis. A review protocol was developed, including scope, databases and criteria guiding the review. Following this, 47 articles were eventually extracted for the systematic review to identify themes for not only addressing the review questions but also highlighting future research opportunities.FindingsIt was found that earlier studies mainly focused on measures, which are designed using mathematical models, management frameworks and other technical support systems, to analyse and evaluate risks, and their impacts on maritime players at the levels of organisation, transport system and region in which the organisation is embedded. There is, however, a lack of research that empirically examines how these measures would contribute to enhancing the resilience performance of maritime firms and their organisational performance as a whole. Subsequently, a Digitally Embedded and Technically Support Maritime Disruption Management (DEST-MDM) model is proposed.Research limitations/implicationsThis review is constrained by studies recorded by the Web of Science only. Nevertheless, the proposed research model would expectedly contribute to enhancing knowledge building in the specific domain of maritime disruption management and supply chain management overall while providing meaningful managerial implications to policymakers and managers in the maritime industry.Originality/valueThis research is perhaps one of the first studies which presents a systematic review of literature in maritime disruption management, and proposes a future research framework that establishes the link between disruption management and resilience and organisational performance for empirical validation.

A REVIEW OF DISRUPTION MANAGEMENT IN VEHICLE ROUTING PROBLEM (VRP), TRANSPORT DESIGN AND SCHEDULING

In the case of an unexpected occurrence, disruption management is a method of rescheduling activities and it has been used in a variety of fields, including organized carrier scheduling and project management. The purpose of this review is to examine Ant Colony Optimization (ACO), the problems of Heuristics for Delivery Waste Collection (VRP), ARC Routing, Node Routing, and Container/skip. Other issues and problems examined in the paper were Non-Skip, Algorithms for the VRP, Improvement Algorithms, Simulated Annealing, and ACO for Capacitated Vehicle Routing, Clustering Analysis, and Probabilistic-D Cluster Analysis. It covers the fundamental characteristics of disruption management as well as the related goals and kinds of disruption that may occur in this setting. The various formulations and solution techniques are discussed in facets. A collection of relevant articles has been summarized and categorized according to the kind of disruption problem being addressed, the relevant goals, and the solution method used to resolve the problem. Vehicles must be emptied at a trash disposal facility before they may be used to collect garbage from further clients. The growing amount of solid waste generated as a result of p

An attention-based view of supply disruption risk management: balancing biased attentional processing for improved resilience in the COVID-19 context

PurposeIn the context of the COVID-19 pandemic, this study investigates a variety of approaches to supply disruption risk management for achieving effective responses for resilience at the supply management subunit level (e.g. category of items). Drawing on the attention-based view of the firm, the authors model the attentional antecedents of supply resilience as (1) attentional perspectives and (2) attentional selection. Attentional perspectives focus on either supply risk sources or supply network recoverability, and both are hypothesised to have a direct positive association with supply resilience. Attentional selection is top down or bottom up when it comes to disruption detection, and these are hypothesised to moderate the association between disruption risk management perspectives and resilience.Design/methodology/approachConducted at the early phases of the COVID-19 pandemic, this study employs a hierarchical regression analysis on a multicountry survey of 190 procurement professionals, each responding from the perspective of their own subunit area of supply responsibility.FindingsBoth attentional disruption risk management perspectives are needed to achieve supply resilience, and neither is superior in terms of achieving supply resilience. Both the efficiency of the top down and exposure to the unexpected with the bottom up are needed – to a balanced degree – for improved supply resilience.Practical implicationsThe results encourage firms to purposefully develop their supply risk management practices, first, to include both perspectives and, second, to avoid biases in attentional selection for disruption detection. Ensuring a more balanced approach may allow firms to improve their supply resilience.Originality/valueThe results contribute to the understanding of the microfoundations that underpin firms' operational capabilities for supply risk and disruption management and possible attentional biases.

Research on disruption management of urgent arrival in job shop with deteriorating effect

A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified.

A Novel Rescheduling Algorithm for the Airline Recovery with Flight Priorities and Airport Capacity Constraints

Many flights experience delays at the airport due to bad weather, temporary closures of airports, unscheduled maintenance, etc., which emphasizes the urgent need for disruption management. It is widely accepted for Chinese airline companies to determine the flight timetable according to the lexicographic preference of flight priorities. Flight schedulers usually deal with the preceding flights as important as the latter flight of a higher priority. In this paper, we propose a build-in flight feasibility verification algorithm to improve the rescheduling algorithm. A novel model of the feasibility verification problem is given, which is equivalent to the model of a maximum clique problem for networks. Examples and tests show the advantage of our algorithm, and the algorithm runs fairly quickly and can be plugged in other scheduling algorithms easily.