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Resource selection/optimization problems are often characterized by two related problems: numerical function and combinatorial optimization. Although techniques ranging from classical mathematical programming to knowledge‐based expert systems (KBESs) have been applied to solve the function optimization problem, there still exists the need for improved solution techniques in solving the combinatorial optimization. This paper reports an exploratory work that investigates the integration of genetic algorithms (GAs) with organizational databases to solve the combinatorial problem in resource optimization and management. The solution strategy involved using two levels of knowledge (declarative and procedural) to address the problems of numerical function, and combinatorial optimization of resources. The research shows that GAs can be effectively integrated into the evolving decision support systems (DSSs) for resource optimization and management, and that integrating a hybrid GA that incorporates resource economic and productivity factors, would facilitate the development of a more robust DSS. This helps to overcome the major limitations of current optimization techniques such as linear programming and monolithic techniques such as the KBES. The results also highlighted that GA exhibits the chaotic characteristics that are often observed in other complex non‐linear dynamic systems. The empirical results are discussed, and some recommendations given on how to achieve improved results in adapting GAs for decision support in the architecture, engineering and construction (AEC) sector.

The issue of the genetic manipulation of plants, animals and microbes is addressed within the context of food production. Genetic manipulation is defined within the wider area of biotechnology and some of the main benefits of its use are summarised; safety and risk are examined and some of the socioeconomic problems it can create are discussed. It is concluded that the technique can offer great potential benefits in terms of increased quantity and improved quality of food, but it raises social/ethical concerns which can be summed up by asking: Is it safe? Is it fair? Is it natural?

A quantitative approach for construction pollution control that is based on construction resource levelling is presented. The parameters of construction pollution index (CPI) and hazard magnitude (hi) are treated as a pseudo resource and integrated with a project’s construction schedule. When the level of pollution for site operations exceeds the permissible limit identified by a regulatory body, a Genetic Algorithm (GA) enhanced levelling technique is used to re‐schedule project activities so that the level of pollution can be re‐distributed and thus reduced. The GA enhanced resource levelling technique is demonstrated using 20 on‐site construction activities in a project. Experimental results indicate that the proposed GA enhanced resource levelling method performs better than the traditional resource levelling method used in MS Project©. The proposed method is an effective tool that can be used by project managers to reduce the level of pollution at a particular period of time; when other control methods fail.

This paper seeks to provide an in‐depth discussion on the impact of agricultural biotechnology in developing and least developed countries (LDCs) as well as the concomitant biosafety concerns that might have an impact on trade and the environment whilst highlighting the importance of choosing development pathways that are conducive to the specific needs of these nations without endangering the biodiversity and affecting people's health.

The paper adopts a socio‐legal approach by undertaking a content analysis of decided cases, relevant treaties and existing studies conducted in areas related to agricultural biotechnology within the framework of sustainable development imperatives.

The paper suggests that developing countries venturing into agricultural biotechnology need to enrich the technology according to their needs and capabilities in order to be able to weigh the benefits against the risks in the production and import of genetically modified organisms (GMOs) specifically via the implementation of the “precautionary principle” and viable “risk assessment” techniques which conform to their existing international law obligations in view of the findings that most of these nations have not formulated adequate legal and institutional frameworks supported with the necessary expertise to regulate, monitor, and ensure safety of agricultural GMOs produced and/or imported by them.

The issues and suggestions in this paper will enable the development process of developing and least developed economies to conform to the tenets of sustainable development and minimize the loss of Earth's biodiversity.

The paper is of practical use to stakeholders and policymakers alike venturing into agricultural biotechnology. It pools the findings of a cross‐section of studies to look at the implications therein and the arising biosafety and trade issues with special reference to developing and LDCs.

This paper aims to investigate and review adaptation measures in the livestock sector from 21 African countries through literature survey and grounded theory approaches. The adaptation themes that emerged captured essence of measures and experience drawn from varied country submissions and contexts instituted to make the livestock sector climate compatible in as far as adaptation is concerned.

Literature survey approach was used on the impacts of climate change on livestock and a review of the submitted adaptation measures. The study used grounded theory approach to derive meaning from the retrieved information. The grounded theory was derived inductively through systematic collection and analysis of data pertaining to the submitted National Communications reports. The retrieved themes were then examined and interpreted to give meaning and draw conclusions through coding, conceptualizing, categorizing and theorizing.

Results identify eight adaptation themes: carrying capacity and policies; integrated pasture management; capacity building, extension, training, awareness and information sharing; livestock breeding, diversification and intensification; disease, vectors and parasites management; technology, innovation, research and development; alternative livelihood; and water supply. The findings show that African Governments have been implementing effective adaptation measures for food security through building a climate resilient livestock production system.

This study is one of the first to lead to recommendations that decision- and policymakers, private sectors, relevant stakeholders and government officials and scientists should play a key role in ensuring that adaptation measures reach farmers, herders at grassroots level. In addition, governments should create an enabling environment (policies) in climate change adaptation to improve food security. These recommendations might be helpful in many communities where adaptation to climate change is a pressing issue.

Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a multi-objectives overall optimization model for project scheduling considering time, cost, resources, and cash flow. This development aims to overcome the limitations of optimizing each objective at once resulting of non-overall optimized schedule.

In this paper, a multi-objectives overall optimization model for project scheduling is developed using particle swarm optimization with a new evolutionary strategy based on the compromise solution of the Pareto-front. This model optimizes the most important decisions that affect a given project including: time, cost, resources, and cash flow. The study assumes each activity has different execution methods accompanied by different time, cost, cost distribution pattern, and multiple resource utilization schemes.

Applying the developed model to schedule a real-life case study project proves that the proposed model is valid in modeling real-life construction projects and gives important results for schedulers and project managers. The proposed model is expected to help construction managers and decision makers in successfully completing the project on time and reduced budget by utilizing the available information and resources.

The paper presented a novel model that has four main characteristics: it produces an optimized schedule considering time, cost, resources, and cash flow simultaneously; it incorporates a powerful particle swarm optimization technique to search for the optimum schedule; it applies multi-objectives optimization rather than single-objective and it uses a unique Pareto-compromise solution to drive the fitness calculations of the evolutionary process.

The purpose of this paper is to develop a qualitative framework for the selection of the most appropriate optimization algorithm for the multi-objective trade-off problem (MOTP) in construction projects based on the predefined performance parameters.

A total of 6 optimization algorithms and 13 performance parameters were identified through literature review. The experts were asked to indicate their preferences between each pair of optimization algorithms and performance parameters. A multi-criteria decision-making tool, namely, consistent fuzzy preference relation was applied to analyze the responses of the experts. The results from the analysis were applied to evaluate their relative weights which were used to provide a ranking to the algorithms.

This study provided a qualitative framework which can be used to identify the most appropriate optimization algorithm for the MOTP beforehand. The outcome suggested that non-dominated sorting genetic algorithm (NSGA) was the most appropriate algorithm whereas linear programming was found to be the least appropriate for MOTPs.

The devised framework may provide a useful insight for the construction practitioners to choose an effective optimization algorithm tool for preparing an efficient project schedule aiming toward the desired optimal improvement in achieving the various objectives. Identification of the absolute best optimization algorithm is very difficult to attain due to various problems such as the inherent complexities and intricacies of the algorithm and different class of problems. However, the devised framework offers a primary insight into the selection of the most appropriate alternative among the available algorithms.

The purpose of this paper is to provide a community perspective on partnerships with the goal of researching, designing, developing and commercializing non‐timber forest products (NTFPs) based on indigenous knowledge and resources from Pikangikum First Nation, northwestern Ontario, Canada.

Framed by the Whitefeather Forest Research Cooperative agreement, a collaborative and ethnographic research design was adopted with the Whitefeather Forest Management Corporation and the Whitefeather Forest Elders Steering Group in Pikangikum First Nation. Over the period of two years, initial research planning meetings were held with community representatives, fieldwork and interviews with community Elders and leaders were conducted, and three community workshops were held.

Community Elders and leaders articulated a cautious interest in developing ethical, collaborative partnerships that support the Whitefeather Forest Initiative and the community's social, cultural, economic and environmental goals. Developing NTFPs through partnerships is a procedural issue that requires giving Elders a primary role in advising and guiding partnerships at all stages of NTFP planning, research and development. Partners would be expected to build respectful and diligent partnerships that interface knowledge systems, maintain good relations, and generate mutually defined benefits.

This community‐specific approach provides insight for Aboriginal groups, governments, universities, and corporations seeking to develop access and benefit sharing agreements, policies, or protocols in light of the Convention on Biological Diversity and the Nagoya Protocol.

This paper offers perspectives, principles, and community member narratives from a Canadian indigenous community, Pikangikum First Nation. These perspectives describe how this community envisions potential research, development and commercialization of NTFPs through joint and mutually beneficial partnerships.

The purpose of this paper is to focus on the analysis of an understudied problem in the economic literature. It proposes a valuation methodology for inputs that come from biodiversity-rich ecosystems/habitats and are used in agro-food production at zero input cost because there is not a market for such inputs.

Following Onofri et al. (2017), the authors computed the value of the marginal productivity of different inputs in three selected case studies (Angola, Mozambique and Brazil). Results are theory based and rigorous but show a strong contingency, case based, relative dimension that is captured, in the framework, by the “relativity ratio.” The ratio expresses the relative weight of the value generated by the input that comes from biodiversity-rich ecosystems/habitats in the per capita monthly available income of the farmer and aims at conveying additional insights to the economic valuation.

In this paper, the assessment of agricultural inputs value (price) in the absence of inputs markets is done, with an application to three different case studies. The inputs are peculiar since they come from habitats and ecosystems that are very biodiversity-rich.

The paper proposes a practical, though rigorous, methodology for the assessment of the value (price) of agricultural inputs in absence of inputs markets. Markets do not exist since the inputs come from biodiversity-rich habitats and ecosystems.

The paper seeks to reflect the information environment with emphasis on indigenous science and technology knowledge requirement in developing countries, particularly India.

Indigenous scientific/technical knowledge functions as a critical national resource for any developing country. Literature reflects need and provision of database services that can cater to indigenous knowledge.

The paper discusses nationally developed databases, various aspects related to initiation and creation of these databases in India. The objectives behind development of such databases and some factors such as indigenous knowledge need, strategic culture, managerial capability, technological thrust and organizational interest responsible for developing databases in India are highlighted. Other features such as quality assessment control and network‐based indigenous knowledge database access and information delivery are discussed. Current indigenous knowledge database activities, efforts of NISCAIR and NISSAT, are highlighted along with promotion and marketing of indigenous knowledge databases. Constraints to indigenous knowledge development in India are discussed. Some guidelines are given to keep balance in the collection and distribution of indigenous knowledge in the developing countries. The paper concludes with the idea of pacing in the right direction for developing balanced and information service‐oriented indigenous knowledge system.

The paper gives an overview of indigenous knowledge database development in India and is useful for librarians to discern the gradual change towards indigenous knowledge storage and to find out the information centers on a national level which can be helpful in indigenous knowledge database development in India.