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The purpose of this paper is to study the problem of clothing uniform assignment (CUA) and propose an immune co‐evolutionary algorithm to search optimal assignments of uniform garments to employees.

Multi‐size fitting measures are proposed based on multi‐attribute decision making. An immune co‐evolutionary algorithm incorporating immune inspired mechanisms is proposed to search optimal assignments.

The experimental results show promising performance. The model and the algorithm are aiming at a valuable problem and can be incorporated into the information systems for large‐scale industrial companies.

Uniform assignment problem is modeled with garment size fitting constraints. Multi‐size fitting measures are proposed based on multi‐attribute decision making and an immune co‐evolutionary algorithm is proposed to search optimal assignments.

This paper aims to review existing wireless sensor network (WSN) setups in various domains, focusing on affordable WSN so that it can be effectively utilised in solving the environmental problems. WSN is being explored in many applications such as home security, smart spaces, environmental monitoring, battlefield surveillance and target tracking. WSN consists of a number of tiny, low-powered, energy-constrained sensor nodes with sensing, data processing and wireless communication components. Creating a WSN setup will make the monitoring system effective and in future, it will give a roadmap for solving some common societal problems.

Various research papers in the area of WSN have been reviewed on the basis of technologies and application on different fields.

WSN was found to be the most effective solution in areas which are less explored due their hazardous nature and are difficult to reach.

This review is based on research papers available and a recent trend in the area of WSN has been explored.

The involvement of the public in the decision-making process is essential, especially in the early stages of a design process. This study aims to achieve the development of an architectural program for a memorial public project, using the outcomes of the Analytical Hierarchy Process (AHP) based on public opinion. It employs a novel approach that sharply focuses on public involvement in the design process, using a quantitative methodology for the development of a suitable building program and selecting a memorial form that meets the public's needs in a practical way. The study drew on data from various memorial projects to identify possible spaces and their selection criteria. A written questionnaire was distributed to a sample of 105 members of the public, to narrow down the number of spaces according to public response. Then, a hearing (spoken) questionnaire was conducted on a sample of 20 to produce the program for development by generating the most strongly preferred form of memorial. The results contradicted the existing norm for a memorial as a sculpture; it was revealed that most of the public preferred memorial landscapes to buildings and great structures. The study concluded that AHP could be used to further involve the relevant stakeholders in the decision-making process of the design of a public project.

It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization problems were being addressed by conventional programming approaches such as Linear Programming, Mixed-Integer Linear Programming and Branch-and-Bound methods. However, the solution convergence in such approaches was slow. But with the advent of Swarm Intelligence (SI)-based algorithms like particle swarm optimization and ant colony optimization, a significant improvement in solution of these problems has been observed. The purpose of this paper is to present and analyze the application of SI algorithms in SCM. The analysis will eventually lead to development of a generalized SI implementation framework for optimization problems in SCM.

A structured state-of-the-art literature review is presented, which explores the applications of SI algorithms in SCM. It reviews 56 articles published in peer-reviewed journals since 1999 and uses several classification schemes which are critical in designing and solving a supply chain optimization problem using SI algorithms.

The paper revels growth of swarm-based algorithms and seems to be dominant among all nature-inspired algorithms. The SI algorithms have been used extensively in most of the realms of supply chain network design because of the flexibility in their design and rapid convergence. Large size problems, difficult to manage using exact algorithms could be efficiently handled using SI algorithms. A generalized framework for SI implementation in SCM is proposed which is beneficial to industry practitioners and researchers.

The paper proposes a generic formulation of optimization problems in distribution network design, vehicle routing, resource allocation, inventory management and supplier management areas of SCM which could be solved using SI algorithms. This review also provides a generic framework for SI implementation in supply chain network design and identifies promising emerging issues for further study in this area.

In recent decades, development of effective methods for optimizing a set of conflicted objective functions has been absorbing an increasing interest from researchers. This refers to the essence of real-life engineering systems and complex natural mechanisms which are generally multi-modal, non-convex and multi-criterion. Until now, several deterministic and stochastic methods have been proposed to cope with such complex systems. Advanced soft computational methods such as evolutionary games (cooperative and non-cooperative), Pareto-based techniques, fuzzy evolutionary methods, cooperative bio-inspired algorithms and neuro-evolutionary systems have effectively come to the aid of researchers to build up efficient paradigms with application to vector optimization. The paper aims to discuss this issue.

A novel hybrid algorithm called synchronous self-learning Pareto strategy (SSLPS) is presented for the sake of vector optimization. The method is the ensemble of evolutionary algorithms (EA), swarm intelligence (SI), adaptive version of self-organizing map (CSOM) and a data shuffling mechanism. EA are powerful numerical optimization algorithms capable of finding a global extreme point over a wide exploration domain. SI techniques (the swarm of bees in our case) can improve both intensification and robustness of exploration. CSOM network is an unsupervised learning methodology which learns the characteristics of non-dominated solutions and, thus, enhances the quality of the Pareto front.

To prove the effectiveness of the proposed method, the authors engage a set of well-known benchmark functions and some well-known rival optimization methods. Additionally, SSLPS is employed for optimal design of shape memory alloy actuator as a nonlinear multi-modal real-world engineering problem. The experiments show the acceptable potential of SSLPS for handling both numerical and engineering multi-objective problems.

To the author’s best knowledge, the proposed algorithm is among the rare multi-objective methods which fosters the use of automated unsupervised learning for increasing the intensity of Pareto front (while preserving the diversity). Also, the research evaluates the power of hybridization of SI and EA for efficient search.

Existing literature acknowledges information systems development (ISD) to be a complex activity. This complexity is magnified by the continuous changes in user requirements due to changing organizational needs in changing external competitive environments. Research findings show that, if this increasing complexity is not managed appropriately, information systems fail. The paper thus aims to portray the sources of complexity related to ISD and to suggest the use of complexity theory as a frame of reference, analyzing its implications on information system design and development to deal with the emergent nature of IS.

Conceptual analysis and review of relevant literature.

This article provides a conceptual model explaining how top‐down “official” and bottom‐up “emergent” co‐evolutionary adaptations of information systems design with changing user requirements will result in more effective system design and operation. At the heart of this model are seven first principles of adaptive success drawn from foundational biological and social science theory: adaptive tension, requisite complexity, change rate, modular design, positive feedback, causal intricacy, and coordination rhythm. These principles, translated into the ISD context, outline how IS professionals can use them to better enable the co‐evolutionary adaptation of ISD projects to changing stakeholder interests and broader environmental changes.

This paper considers and recognizes the different sources of complexity related to ISD before suggesting how they could be better dealt with. It develops a framework for change to deal with the emergent nature of ISD and enable more expeditious co‐evolutionary adaptation.

The cost-oriented robotic assembly line balancing problem (cRALBP) has practical importance in real-life manufacturing scenarios. However, only a few studies tackle the cRALBP using exact methods or metaheuristics. This paper aims to propose a hybrid particle swarm optimization (PSO) combined with dynamic programming (DPPSO) to solve cRALBP type-I.

Two different encoding schemes are presented for comparison. In the frequently used Scheme 1, a full encoding of task permutations and robot allocations is adopted, and a relatively large search space is generated. DPSO1 and DPSO2 with the full encoding scheme are developed. To reduce the search space and concern promising solution regions, in Scheme 2, only task permutations are encoded, and DP is used to obtain the optimal robot sequence for a given task permutation in a polynomial time. DPPSO is proposed.

A set of instances is generated, and the numerical experiments indicate that DPPSO achieves a tradeoff between solution quality and computation time and outperforms existing algorithms in solution quality.

The contributions of this paper are three aspects. First, two different schemes of encoding are presented, and three PSO algorithms are developed for the purpose of comparison. Second, a novel updating mechanism of discrete PSO is adjusted to generate feasible task permutations for cRALBP. Finally, a set of instances is generated based on two cost parameters, then the performances of algorithms are systematically compared.

To better respond to today’s volatile and changing fashion market, the purpose of this paper is to develop a web-based design support system that enables users to design realistic and interesting skirts in the form of technical sketches over the internet.

The proposed system mainly consists of a sketch representation and composing method (SRCM), a graphic user interface (GUI) and a controller. The SRCM is implemented at the server end that generates technical sketches according to user defined parameters and features via the web-based GUI at the client side. The controller manages the workflows between the server and the clients.

To evaluate the effectiveness of the proposed system, a survey was conducted by inviting 30 subjects (professional designers or undergraduate students studying fashion design) to have trial run of the system in Hong Kong and in the USA. Positive comments and feedbacks were received, and valuable suggestions were also obtained in regard to the prototype system.

Compared with traditional computer-aided design (CAD) systems, the proposed system is more effective and easier to operate as users can create technical sketches in accurate proportions with simple computer operations in a few mouse clicks. Besides, the output sketches are fully compatible with most commercial CAD software. The system is developed based on web technologies, thus fashion sketches can be easily designed using any computer connected to the internet; it can be implemented on Android or iOS platform in the future.

This research aims to review how current supply chain management (SCM) research addresses cultural issues, presents a critical assessment of literature and discusses future research avenues.

The literature is reviewed using systematic literature review, bibliometric citation analysis and content analysis. A total of between 1995 and 2019 in Institute for Scientific Information Web of Science’s database.

Descriptive data related to chronological evolution of literature, geographical location, influential papers and methodology are presented. Four main research areas were categorized, namely, papers on SC integration and performance; research on continuous improvement and lean initiatives; studies on the role of culture in sustainability, corporate social responsibility and green practices; and studies on emerging topics of research. Most studies focused on organizational culture frameworks, adopted a static approach to culture and targeted mainly developed countries and Asian emerging countries. A research agenda is suggested based on a multilevel cultural framework including operational and SCM culture.

Practitioners and researchers will gain a greater understanding of how cultural issues have been addressed in current literature. A multilevel framework is proposed based on the concept of “operational” and “SCM culture”, to address some of the issues identified in current literature.

To the best of authors’ knowledge, this study is one of the first literature reviews that considers both national and organizational culture dimensions in SCM research, whereas prior approaches were fragmented or one-dimensional.

Business environments and global transportation system have become more complex than ever due to complexity drivers of industries which create uncertainty and unpredictability to organizations. Like other industries, the maritime business faces different and difficult problems which threaten organizational survival. The ability to cope with those uncertainties, threats and problems shows the resilience ability of organizations that help to survive and prosper. The organizational resilience concept arises as a requirement to deal with problems and uncertainties of business environments which are swiftly changing. This study aims to suggest an organizational framework to show how maritime business organizations as the sea leg of global transportation system can develop resilient organizations via complex adaptive systems (CAS) approach if adequate design features of CAS could be defined and included in organizational properties.

A total of 15 CAS features were identified as the enablers of organizational resilience throughout the literature. An interpretive structural modeling (ISM) approach has been conducted to determine the mutual relation between the CAS features which constitute an organizational framework. These CAS features have been categorized by conducting MICMAC analysis.

This study proposes a framework that identifies CAS features as the enabler of resilient maritime business organizations. The CAS approach offers new managerial toolkit to realize current organizational situations and allows managers to understand that it is difficult to control their system in this dynamic environment where special management practices are required especially in volatile times rather than ordinary times. Also, organizations could not compete as a sole organization but as a web/system of organizations. CAS is more resilient than other systems because resilience is the emergent occurrence of the system formed from nonlinear, dynamic interactions with self-organized agents.

The research has some limitations, like organizational resilience studies are in the infant stage and further research into this area should be extended. This study uses the CAS approach to develop organizational resilience. Further studies could use different lenses and contemporary subjects in management field which should also be useful while developing resilience in organizations. This study uses ISM and MICMAC analysis where further studies could use quantitative design and methods like formal concept analysis or the decision making trial and evaluation laboratory to determine the relational weighs of CAS features while developing resilient organizations. Future studies may also focus on different maritime stakeholders like IMO or ILO, maritime agencies, freight forwarders or insurance underwriters regarding developing and enhancing resilience of the maritime system.

World trade and transportation systems are getting more uncertain and lean on complex relations where maritime transportation is a “vital backbone” of such operations. But becoming more complex structures leads to vulnerable systems and organizations. Most risk management applications are based on predicting the known risks where many of them are not enough to fight with unknowns. Coping with today's problems are difficult for organizations in any industry. But for maritime business stakeholders who work in such a global web of relations, it is much more challenging. So, stakeholders of the system like forwarders, ports or ship chandlers may easily apply those features to develop resilient organizations too. Legal authorities of the system and rule-makers like local Chambers of Shipping, IMO or Classification societies can benefit from this framework and provide supportive settings to develop system-wide resilient organizations.

By understanding environmental uncertainty and complexity better than others, organizations become resilient and cope with significant difficulties which make them more competitive as a substantial strategic advantage. Resilient management offers to break down points at the system and shows them ways to restore quickly while transporting goods while traditional risk assessments are not enough.

The originality of the study lies in two folds; first of all the key and most used features of CAS is linked to developing resilient maritime organizations and by maritime expert opinions, this study tries to determine which of these CAS features are the most effective to trigger other features to develop organizational resilience in the maritime business. And secondly, the concept of organizational resilience and the CAS approach are not analyzed in depth in the context of maritime business.