تکنیک های تصمیم گیری چند معیار (MCDM) ابزار مفید در دستان مدیران پروژه برای غلبه بر مشکلات تصمیم گیری (DM) در پروژه های مهندسی عمران (CEP) می باشد. سهم اصلی این مقاله شامل انتخاب و مطالعه تکنیک های محبوب MCDM است که در انواع گسترده و مختلفی از انواع داده در پروژه های مهندسی عمران استفاده می شود . یک مطالعه دقیق شامل مزایا و معایب استفاده از فرآیند سلسله مراتب تحلیلی (AHP) و تکنیک فازی برای شناسایی ترتیب اولویت ها با شبیه سازی راه حل ایده آل (TOPSIS فازی) معرفی شده است. این دو تکنیک انتخاب شده اند به منظور تشکیل یک بسته که اکثر انواع داده های موجود در پروژه های مهندسی عمران را پوشش می دهد. نتایج نشان داد که AHP دارای یک ساختار است که مشکلات پیچیده را ساده می کند، در حالی که TOPSIS فازی از مزایای متغیرهای زبانی برای حل مسئله داده های مستند نشده و مسائل تبیین نشده استفاده می کند. علاوه بر این، AHP یک روش ساده است که به مقایسه دوگانه عوامل و خصوصیات طبیعی بستگی دارد و در کنار آن سلسله مراتب گسترده را گسترش داد. از سوی دیگر، TOPSIS فازی نیاز به اطلاعات بیشتری دارد، اما برای یک درخت تصمیم گیری یکجانبه خوب عمل می کند و همچنین انعطاف پذیری بیشتری برای کار در محیط های فازی دارد. این دو تکنیک دارای قابلیت تجمیع و ترکیب در یک ماژول جدید برای پشتیبانی از اکثر تصمیمات مورد نیاز در CEP ها هستند.

کلیدواژگان: تصمیم گیری، پروژه های مهندسی عمران, CBA، AHP, Fuzzy TOPSIS

Abstract

Multi-Criteria Decision-Making (MCDM) techniques are found to be useful tools in project managers’ hands to overcome decision-making (DM) problems in Civil Engineering Projects (CEPs). The main contribution of this paper includes selecting and studying the popular MCDM techniques that uses different and wide ranges of data types in CEPs. A detailed study including advantages and pitfalls of using the Analytic Hierarchy Process (AHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is introduced. Those two techniques are selected for the purpose of forming a package that covers most available data types in CEPs.

The results indicated that AHP has a structure which simplifies complicated problems, while Fuzzy TOPSIS uses the advantages of linguistic variables to solve the issue of undocumented data and ill-defined problems. Furthermore, AHP is a simple technique that depends on pairwise comparisons of factors and natural attributes, beside it is preferable for widely spread hierarchies. On the other hand, Fuzzy TOPSIS needs more information but works well for the one-tier decision tree as well as it shows more flexibility to work in fuzzy environments. The two techniques have the facility to be integrated and combined in a new module to support most of the decisions required in CEPs.

Keywords Decision-making,AHP,Fuzzy TOPSIS,CBA,Civil Engineering Projects

۱. Introduction

MCDM is one of the research areas which have been widely studied by researchers and practitioners. It concerns about evaluating, assessing and selecting alternatives from the best to the worst under conflicting criteria with respect to decision maker(s) preferences. The main features of a MCDM technique includes: (1) alternatives, (2) criteria against which the alternatives are evaluated, (3) scores that reflect the value of an alternative’s expected performance on the criteria, and (4) criteria weights that measure the relative importance of each criterion as compared with others (Celik et al., 2012). There are several MCDM techniques proposed by researchers in literature but here, the paper focuses on helping decision maker to select the most appropriate technique based on the given problem characteristics, especially in CEPs, and the type of available data.

A popular belief appears to be that any DM technique is as good as another, so it does not matter which one is selected (Azapagic and Perdan, 2005). In contrast, (Okudan and Tauhid, 2008) mentioned that “different techniques tend to produce different outcomes for selecting decision alternatives”. (Suhr, 1999) stated that DM techniques result in people making decisions. Decisions produce actions and actions cause outcomes; consequently, if outcomes matter, then the selection of the DM technique also matters. Thus, the choice of selecting a suitable DM technique in itself is a critical decision as different techniques yield different solutions. It is imperative for the decision maker to be aware of the underlying principle used in a technique, and the pitfalls associated with (Okudan and Tauhid, 2008).

This paper consists of four main sections: (1) DM techniques classifications, (2) the most applied techniques to CEPs, (3) applications of DM techniques to CEPs, and (4) selecting and comparing the most used techniques and the data type they need.