Simple multi-attribute rating technique for renewable energy deployment decisions (SMART REDD)

Abstract

In the effort to provide electrical power service and the sustaining fuel required to run generators at forward-deployed bases in Afghanistan and Iraq over more than 10 years, the US military spent billions of dollars and a paid a heavy toll in terms of human casualties. The green energy linear program for optimizing deployments (GELPOD) proof-of-concept model showed that a linear program could be used to optimize combat deployment of energy generation systems to minimize cost and casualties. Results indicated that reduction in both cost and casualties for renewable energy sources was highly dependent on fuel cost and deployment length. Neglected in the decision making process, however, were factors that impact the operational success of the mission. When deploying combat units, commanders must not only consider potential costs and casualties, they must also contend with battlefield mobility requirements, maintenance capability (or lack thereof), weather, and anticipated hostile action that could affect operational performance. This paper leverages the simple multi-attribute rating technique (SMART), pioneered by Edwards, to attempt to address this deficiency. The resulting simple multi-attribute rating technique for renewable energy deployment decisions (SMART REDD) model allows commanders to take mission attributes into consideration when making decisions on which energy source is most appropriate for the mission as well as providing information on operations costs, expected transportation requirements, and expected casualties.

Implementasi Simple Multi Attribute Rating Technique Untuk Penentuan Tempat Pembuangan Akhir

“…Rencana volume sampah di Kabupaten Pemalang sampai dengan Tahun 2030 adalah sebagai berikut [1] : Pada himpunan data diperlukan sebuah sistem untuk melakukan pendataan, pengelolan dan pemetaan terhadap penentuan Tempat Pembuangan Akhir yang akan digunakan untuk membaca data agar lebih mudah ditampilkan secara visual. Seperti yang terdapat pada Negara Amerika yang memanfaatkan sistem pendukung keputusan untuk menentukan pengembangan energi terbaharukan menggunakan metode Simple Multi-Attribute Rating Technique di mana terdapat 7 parameter dan data atribut biaya serta dampaknya selama 5 tahun, didapatkan bahwa metode ini sangat berguna untuk merencanakan dan memberikan perintah untuk mendukung produksi operasional [2] .…”

“…Metode SMART (Simple Multi-Attribute Rating Technique) adalah metode yang digunakan untuk membuat keputusan dengan penyelesaian multi kriteria paling sederhana untuk merespon kebutuhan yang mendesak [9] dibandingkan metode Simple Addictive Weighting (SAW) dan Analytics Hierarchy Process(AHP) [2] . Relevan untuk diimplementasikan dalam menunjang teknologi untuk menentukan lokasi terbaik dengan kesederhanaan penentuan keputusan Metode SMART [10] .…”

Weak and Strong Compensation for the Prioritization of Public Investments: Multidimensional Analysis for Pools

“…The main application of SMART is on environmental management decisions [40][41][42], but it is also proposed for a public assessment application for mitigation and adaptation policy [43], as well as transport [44]. On an urban scale, it is used in assessing the sustainability of built heritage [45], local energy systems [46] and urban ecosystems [47][48][49][50].…”

Research of Simple Multi-Attribute Rating Technique for Decision Support

“…SMART (Simple Multi Attribute Rating Technique) is a multi-criteria decision method developed by Edward in 1977 [1] [7]. This multi-criteria decision-making technique is proposed on the theory that each alternative consists of some criteria that have values and each criterion have weights that describe how important compared to other criteria.…”

“…The decision support system that will introduce in this research use SMART method which aims to gather information about all data related to multiple attributes and multiple-criteria [7]. The data in the parameters is the data of the past and the future, from the data, will be generated classification and the relationship between data one and other data so that the final result will get the best results solution, choosing SMART (Simple Multi Attribute Rating Technique) method because this method can make multi-decision decisions, so it is expected to create an accurate decision-making system and can solve the problem of decision making the best [7] [8] [9] [10].…”