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In this paper, stochastic optimisation and risk estimation techniques are applied to the problem of hydroelectric generator design. Optimisation results from deterministic simulations can involve considerable risks due to unavoidable variations in system properties as well as environmental conditions. Therefore, stochastic simulation is used to include the effects of parameter scatter and noise effects in the computer models. This allows the evaluation of the scatter in performance and thus an assessment of reliability and quality of the simulated system.

The purpose of this paper is to find a global method for the limited K‐partitioning of hypergraphs representing optimal design problems in complex machine systems.

To represent some real design considerations, a new concept of semi‐free hypergraphs is proposed and a method to apply semi‐free hypergraphs to the decomposition of complex design problems based on optimal models is also suggested. On this basis, the limited K‐partitioning problem of semi‐free hypergraphs and its partitioning objective for the optimal design of complex machines is presented. A global method based on genetic algorithms, GALKP, for the limited K‐partitioning of semi‐free hypergraphs is also proposed. Finally, a case study is presented in detail.

Semi‐free hypergraphs are a more powerful tool to map a complex engineering design problem. The decomposition of complex design problems may be converted to a limited K‐partitioning problem of semi‐free hypergraphs. The algorithm presented in this paper for the limited K‐partitioning of semi‐free hypergraphs is fast, effective, and powerful.

The traditional methods based on hypergraphs have some limitations while applied to the decomposition of some complex problems such as the design of large‐scale machine systems. The proposed method is helpful to solve similar engineering design problems.

The paper illustrates a faster and more effective method to implement the decomposition of large‐scale optimal design problems in complex machine systems.

This paper shows a new way to solve the complex engineering design problems based on semi‐free hypergraphs and its K‐partitioning method.

Instant crowdsourcing logistics (ICL) platform is an emerging business model in the field of logistics services. Crowdsourcees’ active participation in platform value co-creation is the key to success for this business model. This study aims to explore the influence of platform governance mechanisms on crowdsourcees’ participation in value co-creation on the platform.

Based on governance theory, this study constructed a model of the influence of platform governance mechanisms on crowdsourcees’ value co-creation intentions and discussed the role of community diversity in this model. The survey data of 319 collected from crowdsourcees on China’s well-known ICL platform were analyzed using a partial least squares structural equation model.

The results showed that platform governance mechanisms have a significant influence on crowdsourcees’ value co-creation intentions. Among them, the impact of the welfare resource support mechanism is the largest, followed by the reputation reward and punishment mechanism, while the price coordination mechanism has the least impact. Community diversity has a significant positive moderating effect on the welfare resource support mechanism and crowdsourcees’ value co-creation intentions, but not between other governance mechanisms and crowdsourcees’ value co-creation intentions.

The results provide references for ICL platform to develop a targeted governance mechanism to enhance the positive role of community diversity and reduce the negative impact.

Users’ active participation in platform value co-creation is the key to the development of crowdsourcing logistics platforms, especially the active participation of the crowdsourcee who provide logistics services. However, driven by self-interest, coupled with loose links among subjects on the platform ecological chain, it is difficult for users to effectively form value co-creation intentions. This study aims to explore how platform governance affects crowdsourcees’ intention to participate in value co-creation on the platform through individual cognition.

Based on social cognitive theory (SCT), this study built a research model and took the crowdsourcee on China’s well-known crowdsourcing logistics platforms as the investigation object, using the collected 302 valid survey data to test the model.

The results showed that platform governance mechanisms have a significant influence on crowdsourcees’ intention to participate in value co-creation on the platform, either directly or through crowdsourcee cognition, and the impact is different. The crowdsourcee cognition plays a mediating role between platform governance mechanisms and crowdsourcees’ intention to participate in value co-creation on the platform, and the mediating effect of value acquisition perception (VAP) is significantly higher than self-efficacy (SE).

The results provided references for crowdsourcing logistics platforms to develop a targeted governance mechanism to promote the platform to achieve value co-creation.

Is the rise of the Indian software industry simply another Asian state-dominated industrial growth story or is India distinctive, an economy where small technology entrepreneurs also find niches for development and can be drivers of innovation? Research has focused on the large integrated Indian and international service providers. This study examines the opportunity for growth among smaller innovative technology entrepreneurial firms. Two areas of inquiry are: What factors have been responsible for spurring growth in the Indian IT industry? What type of work is being carried out at Indian firms and is this profile changing? This paper aims to examine the emergence of technology entrepreneurs, particularly in terms of their links to multinational firms and their role and position in global value chains. The paper takes a multi-level approach to understanding development trajectories in the IT sector in India: a global value chain approach to the extent that company processes are seen in their larger networked context across organizations and an institutional approach in terms of state policies that influence the creation of infrastructure that, in turn, shapes organizational development trajectories. Additionally, it examines the role of the various actors within IT sector organizations – the workers, the managers and, in the case of the small companies in our sample, the owners – on the outcome of growth trajectories in the Indian IT sector. We find that the various levels of change and policy all contribute to the outcome in company trajectories: the dominance of multinational enterprises on the market, the entrepreneurial vision and survival strategies of returned technology expatriates, and the changing policies of the government in promoting indigenous business.

Qualitative research interviews; comparative case study; literature review; multi-tier analysis.

The technology entrepreneurial development in India appears to represent quite a distinctive path in terms of both firm development and broader economic development. It is focused on the IT sector, in which high skill “knowledge work” is carried out and which has been able to develop despite lack of basic infrastructure (roads and reliable electricity).

After the opening up of the business environment to large Western multinational enterprises (MNEs), it was difficult for indigenous Indian entrepreneurs to compete in innovative product development markets. Developing such companies depended on individual risk taking, as no specific infrastructure existed for niche production. However, the knowledge base and innovation clusters did offer opportunities for obtaining contracts. The Indian entrepreneurs did have to make a lot of compromises about defining their business and the tasks they could undertake. More research is needed on the paths and development opportunities for these smaller Indian-owned firms.

Unique opportunities are emergent and defy easy policy prescriptions, other than precluding change that does not foreclose emergent possibilities (e.g. such as strong state controlled business development).

Indian-owned innovative companies, although having difficulties competing with large Indian and Western MNEs, do put pressure on these MNEs to move work up the value chain, thereby providing more interesting and challenging opportunities for Indian knowledge workers.

This paper provides a unique company-level perspective about entrepreneurialism in the Indian software sector from the perspective of different actors in the process. It then links this company-level perspective to a larger context both in terms of trajectories of development at the macro level, as well as the role that the company’s place in multinational value chains has in its development perspectives. It gives a special insight into the motivations and obstacles facing entrepreneurs in India’s dynamic software sector.

The purpose of this paper is to propose a numerical algorithm able to describe the Stackelberg strategy for a multi level hierarchical three-person game via genetic algorithm (GA) evolution process. There is only one player for each hierarchical level: there is an upper level leader (player L0), an intermediate level leader (player L1) who acts as a follower for L0 and as a leader for the lower level player (player F) that is the sole actual follower of this situation.

The paper presents a computational result via GA approach. The idea of the Stackelberg-GA is to bring together GAs and Stackelberg strategy in order to process a GA to build the Stackelberg strategy. Any player acting as a follower makes his decision at each step of the evolutionary process, playing a simple optimization problem whose solution is supposed to be unique.

A GA procedure to compute the Stackelberg equilibrium of the three-level hierarchical problem is given. An application to a Authority-Provider-User (APU) model in the context of wireless networks is discussed. The algorithm convergence is illustrated by means of some test cases.

The solution to each level of hierarchy is supposed to be unique.

The paper demonstrates the possibility of using computational procedures based on GAs in hierarchical three level decision problems extending previous results obtained in the classical two level case.

This paper proposes a bar‐system graph representation for structural topology optimization using a genetic algorithm (GA).

Based on graph theory, a graph is first used to represent a skeletal structure consisting of joining paths in the design domain, each of which is represented by a chain subgraph with finite number of vertices. Based on the edges of this graph, a bar‐system representation is proposed to define all the bars and the resulting topology is obtained by mapping each bar with its corresponding thickness to the design domain which is discretized into a regular mesh. The design variables are thus reduced to the spatial distribution of the vertices and the thickness of each bar. This method combines the advantages of both continuum and ground structure optimization methods.

The overall procedure is applied to classical structural topology optimization problems and its good performance is illustrated in the numerical examples.

It is suggested that the present representation method is both physically meaningful and computationally effective in the framework of topological optimum design using GAs.

A multi-objective mixed-integer linear program (MILP) model is developed to address this problem. The primary objective is to minimize the total restructuring cost, while the secondary objective aims to enhance the customer service level. To tackle the NP-hard nature of the problem, the non-dominated sorted genetic algorithm (NSGA-II) and a hybrid NSGA-II with the ɛ-constraint method are employed. The hybrid method combines the strengths of the ɛ-constraint method with NSGA-II. Various performance metrics, including the number of Pareto solutions (NPS), normalized set coverage and spacing metrics, are utilized to compare the characteristics of the non-dominated fronts obtained by NSGA-II and the hybrid methods.

The Restructuring Facility Location Problem involves the closure, resizing or opening of a group of facilities and the assignment of customers to these selected facilities. The objective is to provide the required service to customers while minimizing the overall restructuring costs. This paper introduces a novel multi-objective model for hierarchical facilities called the Multi-Objective Restructuring Hierarchical Facility Location Problem (MO-RHFLP). The model specifically includes primary- and secondary-level facilities, with the primary facility offering broad coverage. In MO-RHFLP, customers within the coverage range of the primary facility can receive service from there.

The results demonstrate that the NSGA-II-based method performs well in terms of normalized set coverage and spacing metrics. However, the hybrid method outperforms NSGA-II in these aspects. Additionally, the hybrid method achieves a mutation in the NPS metric.

The present study, from three perspectives, has continued the way of the previous studies in restructuring channels. First, the multi-objective problem of restructuring the bi-level network executed in this study contains both levels of the network opening, closing and resizing. Taking a different perspective, the MO-RHFLP problem is introduced through the formulation of a multi-objective MILP model. This model serves as a framework for addressing the MO-RHFLP. By developing the hybrid ɛ-constraint method with NSGA-II, we solve the proposed problem.

The purpose of this paper is to propose variants of an adaptive penalty scheme for steady-state genetic algorithms applied to constrained engineering optimization problems.

For each constraint a penalty parameter is adaptively computed along the evolution according to information extracted from the current population such as the existence of feasible individuals and the level of violation of each constraint. The adaptive penalty method (APM), as originally proposed, computes the constraint violations of the initial population, and updates the penalty coefficient of each constraint after a given number of new individuals are inserted in the population. A second variant, called sporadic APM with constraint violation accumulation, works by accumulating the constraint violations during a given insertion of new offspring into the population, updating the penalty coefficients, and fixing the penalty coefficients for the next generations. The APM with monotonic penalty coefficients is the third variation, where the penalty coefficients are calculated as in the original method, but no penalty coefficient is allowed to have its value reduced along the evolutionary process. Finally, the penalty coefficients are defined by using a weighted average between the current value of a coefficient and the new value predicted by the method. This variant is called the APM with damping.

The paper checks new variants of an APM for evolutionary algorithms; variants of an APM, for a steady-state genetic algorithm based on an APM for a generational genetic algorithm, largely used in the literature previously proposed by two co-authors of this manuscript; good performance of the proposed APM in comparison with other techniques found in the literature; innovative and general strategies to handle constraints in the field of evolutionary computation.

The proposed algorithm has no limitations and can be applied in a large number of evolutionary algorithms used to solve constrained optimization problems.

The proposed algorithm can be used to solve real world problems in engineering as can be viewed in the references, presented in this manuscript, that use the original (APM) strategy. The performance of these variants is examined using benchmark problems of mechanical and structural engineering frequently discussed in the literature.

It is the first extended analysis of the variants of the APM submitted for possible publication in the literature, applied to real world engineering optimization problems.

Cosmology is of essence for the life of traditional man not only to live in a meaningful universe, but to bound himself with the universe to achieve well-being as well. Architecture is a way of creating spaces through generic forms and symbols to attain this unity of man and the universe. This article interprets the courtyard house which is a well known archetype of spiritual and celestial qualities and has symbolic generic forms through the perspective of theory and practice of feng shui which is an ancient Chinese philosophy, based on the understanding of physical configuration of geographical settings and application of its principles to the built environment. The courtyard houses represented for this article are chosen on a linear axis starting from Cyprus, passing through Syria, Iraq, Iran, Afghanistan, Pakistan, India, and ending at China. In this article, principles of feng shui are selected and formulated to create an evaluation model showing entrance-courtyard relation, building shape, water element, room arrangement, and door alignment and circulation. Based on this evaluation model, the essential aspects of well-being have been revealed through the elements of architecture. In that sense, this article presents the opportunities and possibilies of an ideal plan layout by bringing an awareness to the cosmology and feng shui to achieve well-being.