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Project managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time–cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time–cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called “multiple-objective social group optimization” (MOSGO) for optimizing time–cost decisions in generalized construction projects.

In this paper, a novel MOGSO to mimic the time–cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution.

Two case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time–cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.

Accordingly, the first major practical contribution of the present research is that it provides a tool for handling real-world construction projects by considering all types of construction project. The second important implication of this study derives from research finding on the hybridization multiple-objective and multi-criteria techniques to help project managers in facilitating the time–cost tradeoff (TCT) problems easily. The third implication stems from the wide-range application of the proposed model TCT.

The model can be used in early stages of the construction process to help project managers in selecting an appropriate plan for whole project lifecycle.

The proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research.

This paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.

Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).

A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.

Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.

It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.

An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

The purpose of this paper is to develop a mathematical model that determines the location of temporary logistics hubs (TLHs) for disaster response and proposes a new method to determine weights of the objectives in a multi-objective optimization problem. The research is motivated by the importance of TLHs and the complexity that surrounds the determination of their location.

A multi-period multi-objective model with multi-sourcing is developed to determine the location of the TLHs. A fuzzy factor rating system (FFRS) under the group decision-making (GDM) condition is then proposed to determine the weights of the objectives when multiple decision makers exist.

The interview with decision makers shows the heterogeneity of decision opinions, thus substantiating the importance of GDM. The optimization results provide useful managerial insights for decision makers by considering the trade-off between two non-commensurable objectives.

In this study, decision makers are considered to be homogeneous, which might not be the case in reality. This study does not consider the stochastic nature of relief demand.

The outcomes of this study are valuable to decision makers for relief distribution planning. The proposed FFRS approach reveals the importance of involving multiple decision makers to enhance sense of ownership of established TLHs.

A mathematical model highlighting the importance of multi-sourcing and short operational horizon of TLHs is developed. A new method is proposed and implemented to determine the weights of the objectives. To the best of the authors’ knowledge, the multi-actor and multi-objective aspects of the TLH location problem have not thus far been considered simultaneously for one particular problem in humanitarian logistics.

The purpose of this paper is to improve current design processes by proposing a new approach based on multi‐criteria optimization of the designed asset. Management of design in construction projects is a complex task since it involves collaboration between professionals in multiple disciplines. Traditionally, designers work with a single solution at a time which is iteratively modified according to the view points of all the consultants. This results in sub‐optimal solutions. A multi‐criteria approach is able to accommodate diverse view points of specialist consultants in a construction project, aiming at a better optimized building system.

The shortcomings of current design practices are analyzed based on a literature review. It is found that current approaches involving single objective optimization or Pareto optimization are not adequate for supporting collaborative design processes. A new approach to managing multiple objectives in design is proposed. This involves performing multi‐objective optimization, presenting a population of good solutions to the design consultants and selecting the best solution through an algorithm called RR‐PARETO2 (Relaxed‐Restricted Pareto) filtering. A software tool with a graphical user interface was developed. An example of the design of a building façade is taken to evaluate the application of this approach.

The paper provides empirical evidence that a multi‐objective optimization approach is able to provide support for the task of accommodating multiple viewpoints in design. The proposed methodology allows navigation through the solution space and pruning it visually by applying constraints. It is shown that the RR‐PARETO2 is able to select a good compromise solution with the best trade‐offs among all the objectives.

The idea of visualizing and filtering a population of design solutions has been proposed by design researchers for a long time, but is not currently adopted in practice in construction projects. The idea of collaborative filtering of the solution space according to the viewpoints of all the consultants by visually applying constraints on design variables and objectives is a new concept, the ultimate aim being a better balanced built asset. This is the first time the RR‐PARETO2 algorithm has been applied to building design.

Processes, in practice, may involve more than one quality characteristic that are of interest. It is quite possible for such quality characteristics to not be independent of each other since the magnitude of one of the characteristics may influence the magnitude of the other characteristics. Under this setting, it is of interest to determine the optimal settings of the process parameters (usually the process mean and the process standard deviation of each quality characteristic) under various objectives. Some of the objectives may be conflicting to each other. In general, it may be possible for the decision-maker to prioritize the objectives. Using such a prioritized scheme, it is of interest to determine the optimal settings of the process mean and standard deviation for each quality characteristic that is being monitored. Such solutions could be labeled as “satisficing” solutions. Sensitivity analyses of the decision variables to the chosen objectives and parameter values are also investigated.

There are many investigations in design methodologies, but there are also divergences and convergences as there are so many points of view. This study aims to evaluate to corroborate and deepen other researchers’ findings, dissipate divergences and provide directing to future work on the subject from a methodological and convergent perspective.

This study analyzes the previous reviews (about 15 reviews) and based on the consensus and the classifications provided by these authors, a significant sample of research is analyzed in the design for additive manufacturing (DFAM) theme (approximately 80 articles until June of 2017 and approximately 280–300 articles until February of 2019) through descriptive statistics, to corroborate and deepen the findings of other researchers.

Throughout this work, this paper found statistics indicating that the main areas studied are: multiple objective optimizations, execution of the design, general DFAM and DFAM for functional performance. Among the main conclusions: there is a lack of innovation in the products developed with the methodologies, there is a lack of exhaustivity in the methodologies, there are few efforts to include environmental aspects in the methodologies, many of the methods include economic and cost evaluation, but are not very explicit and broad (sustainability evaluation), it is necessary to consider a greater variety of functions, among other conclusions

The novelty in this study is the methodology. It is very objective, comprehensive and quantitative. The starting point is not the case studies nor the qualitative criteria, but the figures and quantities of methodologies. The main contribution of this review article is to guide future work on the subject from a methodological and convergent perspective and this article provides a broad database with articles containing information on many issues to make decisions: design methodology; optimization; processes, selection of parts and materials; cost and product management; mechanical, electrical and thermal properties; health and environmental impact, etc.

This paper aims to further improve the efficiency of multi-objective optimization design of synchronous reluctance motors (SynRMs) using the level set (LS) method, which has the advantage of obtaining a practical shape. The solutions obtained by gradient methods tend to be local ones due to the multi-modality of the objective function, especially when multiple objective functions. A huge number of trial calculations are required to obtain a high-quality and broadly distributed Pareto front. Therefore, it is indispensable to effectively get out of the local solutions in the optimization process with the LS method.

The authors propose a novel method appropriately switching multiple objective functions with high independence of sensitivity information. The authors adopt highly independent mathematical expressions for the objective functions of the average torque and torque ripple. In addition, the authors repeatedly perform the optimization while appropriately selecting the sensitivity information of one objective function from multiple ones, which enables the authors to effectively break out of local solutions in the optimization process.

The proposed method was applied to the shape optimization of SynRM flux barriers and successfully searched a more extensive and advanced Pareto front in comparison with the conventional method.

The proposed method adopts search spaces with mathematical high independence for average torque and torque ripple. In the optimization process, when the solution search is judged to get stuck by several criteria, the search space is alternately switched to effectively get out of local solutions.

The paper seeks to provide academic researchers and practitioners with a better understanding about purchasing strategies through an integrated approach to supplier selection and purchasing decisions.

This paper views supplier selection as a multi‐criteria problem. Through the analytical hierarchy process (AHP), in consideration of both quantitative and qualitative criteria, a set of candidate suppliers is identified. A multi‐objective linear programming (MOLP) model, with multiple objectives and a set of system constraints, is then formulated and solved to allocate the optimum order quantities to the candidate suppliers.

The paper provides tradeoffs among different objectives, which are more consistent with the complexity and nature of the real‐world decision‐making environment. It also offers better information and solutions supporting effective purchasing decisions.

The main concept of the proposed approach can be applicable to any organization with a purchasing function. However, its implementation will be very specific to a particular organization of interest, as each individual organization must define its own subjective criteria and constraints. The area of decision support system development, which automates (or computerizes) the input process of the proposed models and integrates with other databases in a company, will provide great opportunities for future research.

The paper provides practitioners with flexibility and effectiveness in their supplier selection and purchasing decision process and with a better understanding about their future purchasing strategies. The results from the application of the proposed models to the supplier selection problem at a high‐technology firm in Taiwan show that the models are effective and applicable.

This paper takes an integrated approach to problem analysis (i.e. multi‐objectives with both quantitative and qualitative information), uses a sound scientific methodology in model development (i.e. integrating AHP with MOLP), and provides practical use of the models. It offers additional knowledge and value to both academics and practitioners.

The purpose of this paper is to adopt an agency theory approach to investigate the integration of environmental issues into management control systems (MCS). Prior environmental accounting research has focussed on increasing organisations’ environmental accountability by “monitoring” through external reporting to stakeholders. However, this overlooks the alignment of agents’ interests within the firm.

A qualitative case study is undertaken in a large Australian listed property trust to investigate how agents’ interests may be integrated with environmental objectives through the use of MCS.

From the case an analytical framework is developed to illustrate how environmental issues are incorporated into organisational behaviour through MCS. The findings include, single objective environmental MCS; multiple objective MCS, which include priorities that specify environmental and economic trade-offs; and balancing MCS, which provide overarching decision-making principles without priorities.

The findings provide examples of how an organisation may integrate environmental issues across a range of MCS and the things to consider in doing so.

This paper draws on an agency perspective as an approach to incorporate environmental issues into MCS and to align behaviour. It explains a new way in which tensions can be managed. This study is one of the first to adopt the control package approach in investigating the incorporation of environmental issues in MCS.

Argues that the general area of commercial sponsorship activity, while attracting increasing interest from marketing practitioners as an important strategic option in marketing communications, has not been the subject of sufficiently rigorous and comprehensive investigation by theoreticians. States the purpose is to establish and consolidate the available body of knowledge combining an overview of the standard conceptual approaches to marketing communication with an examination of the recent academic research in sponsorship, while maintaining a focus on current marketplace practice. Argues for a coherent and structured approach to the management of sponsorship expenditure through the application of a ‘management by objectives’ approach. Parameters are established in terms of a working definition of sponsorship, a review of its commercial development and an overview of current activity. Develops a commercially ration framework within which sponsorship activity may be undertaken. Views objective‐setting as the cornerstone of sponsorship management and outlines a classification of sponsorship objectives that subsumes current practice clarifies the range of potential benefits. Examines the criteria that govern rational sponsorship selection and proposes an evaluation strategy based on stated criteria. Methods of evaluating effects of marketing communications (sponsorship particularly) are examined and new evaluation techniques are advanced to facilitate the implementation of this rigorous scientific approach.