Economy-energy trade off automation – A decision support system for building design development

2020 ◽  
Vol 30 ◽  
pp. 101222
Author(s):  
Mazdak Nik-Bakht ◽  
Rafaela Orenga Panizza ◽  
Philippe Hudon ◽  
Pierre-Yves Chassain ◽  
Masoud Bashari
2004 ◽  
Vol 20 (03) ◽  
pp. 147-163
Author(s):  
Osman Turan ◽  
Selim Alkaner ◽  
Aykut i. Ölçer

Ship design today can be viewed as an ad hoc process. It must be considered in the context of integration with other design development activities, such as production, costing, quality control, and so forth. Otherwise, it is possible for the designer to design a ship that is difficult to produce, requires high material or labor cost, or contains some design flaws that the production engineers have to correct or send back for redesigning before production can be done. Any adjustment required after the design stage will result in a penalty of extra time or cost. Deficiencies in the design of a ship will influence the succeeding stages of production. In addition to designing a ship that fulfills producibility requirements, it is also desirable to design a ship that satisfies risk, performance, cost, and customer requirements criteria. More recently, environmental concerns, safety, passenger comfort, and life-cycle issues are becoming essential parts of the current shipbuilding industry. Therefore, "design for X paradigm" should also be considered during the ship design stages. An integrated multiple attributive decision support system for producibility evaluation in ship design (PRODEVIS) is developed to use by industry and researchers in evaluating the producibility of competing ship designs and design features during the early stages of ship design by taking into account cost, performance, risk, and "design for X paradigm" attributes. This developed approach is a fuzzy multiple attributive group decision-making methodology where feasible design alternatives are conducted by a ship production simulation technique. In this approach, an attribute-based aggregation technique for a heterogeneous group of experts is employed and used for dealing with fuzzy opinion aggregation for the subjective attributes of the ship design evaluation problem. The developed methodology is illustrated with a case study.


2018 ◽  
Author(s):  
Caleb Fink ◽  
Bo Liu ◽  
Fletcher Easton ◽  
Chandra Krintz ◽  
Rich Wolski ◽  
...  

Author(s):  
G Michael McGrath ◽  
Geoffrey H Lipman

For design, development, implementation and use of an information system (IS) to constitute a valid research activity, the system should support the solution of a non-trivial and important problem and it should be original, drawing on existing theories and knowledge. The design of one such system is described in this paper: specifically, a decision support system (DSS) designed to support the development of ‘Green Growth’ (GG) strategies for Travelism (Travel & Tourism) destinations. A sound GG strategy is important: first, because tourism is a major contributor to the global economy - particularly for developing and island states; second because it represents some 5% of greenhouse gas (GHG) emissions and these are increasing faster than the global norm; and third because the environment is an essential element of destination attractiveness. Thus, the problem domain is certainly non-trivial and important. It is further argued that the design of the DSS artefact described is original and novel in the sense that: i) it supports the entire GG strategy development process (which is actually cyclical); ii) it allows for the sharing of data, functionality and knowledge between different DSS applications and different strategy development exercises in a seamless, integrated manner; and iii) it will be deployed in a global community based program in 2016. System design draws heavily on previous IS, information management and software engineering research; particularly with regard to use of abstraction and interfaces in support of component sharing and reuse.


2017 ◽  
Vol 28 (6) ◽  
pp. 737-748 ◽  
Author(s):  
Ganda Boonsothonsatit

Purpose This paper explains the development stages of a generic decision support system to leverage supply chain performance (GLE). The purpose of this paper is to identify and trade off the critical supply chain measures which are interrelated and in contradiction with each other. Design/methodology/approach The GLE was developed as an extension of the supply chain performance assessment tool proposed by Banomyong and Supatn (2011). It contained nine measures covering key activities along the supply chain under dimensions of cost, time and reliability. Their interrelations were figured out by causal linkages, whereas their contradictions were traded off as multi-objective optimization. It is solved using fuzzy goal programming along with a weighted max-min operator in order to acquire the Pareto-optimal solution. Findings The results from the GLE showed there were two critical supply chain measures including supply chain cost per sales and average order cycle time. They contradictorily influenced by a root-cause, namely product lot size. Its Pareto-optimal value was provided to achieve the minimized values of supply chain cost per sales and average order cycle time which were consistent with their relative weights. Research limitations/implications As generic features, the GLE needs further validation in several industries under various supply chain strategies. The further validation may contribute the GLE to include multiple decision variables, multiple types of product and multiple periods of time. In addition, the GLE may consider a dimensional measure of environmental impact along the supply chain activities. Originality/value The GLE is a unique decision support system to identify and trade off the critical, interrelated and contradicting supply chain measures. More uniqueness is obtained when the GLE offers an option of inputting a set of relative weights for the interrelated supply chain measures.


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