Short answer

When selecting critical infrastructure locations, employ hybrid MCDA models that incorporate expert judgment and fuzzy logic to systematically evaluate multiple, potentially conflicting criteria.

Field: Modelling
Source: International Journal of the Analytic Hierarchy Process (2023)
Method: Hybrid Multi-Criteria Decision Analysis (MCDA) using Spherical Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
Evidence: Strong effect

A multi-criteria decision-making model combining Spherical Fuzzy AHP and TOPSIS can effectively identify optimal locations for parcel pick-up points by systematically evaluating complex factors. This modelling research insight is drawn from a 2023 study published in International Journal of the Analytic Hierarchy Process. Using Hybrid multi-criteria decision analysis (mcda) using spherical fuzzy analytic hierarchy process (ahp) and technique for order preference by similarity to ideal solution (topsis)., researchers explored how this design variable affects real-world outcomes. The key design takeaway: When selecting critical infrastructure locations, employ hybrid MCDA models that incorporate expert judgment and fuzzy logic to systematically evaluate multiple, potentially conflicting criteria.

Study

ModellingRecentStrong effect

Hybrid AHP-TOPSIS Model Optimizes Parcel Pick-Up Point Locations

A multi-criteria decision-making model combining Spherical Fuzzy AHP and TOPSIS can effectively identify optimal locations for parcel pick-up points by systematically evaluating complex factors.

International Journal of the Analytic Hierarchy Process · 2023

Key Findings

01The hybrid Spherical Fuzzy AHP-TOPSIS model successfully ranked potential parcel pick-up point locations.
02Kadikoy, Umraniye, and Atasehir were identified as the most ideal locations in Istanbul based on the applied criteria.

Application

Design takeaway

When selecting critical infrastructure locations, employ hybrid MCDA models that incorporate expert judgment and fuzzy logic to systematically evaluate multiple, potentially conflicting criteria.

How to apply

Adapt the Spherical Fuzzy AHP-TOPSIS framework to identify optimal locations for new service points, distribution centres, or retail stores by defining relevant criteria and gathering expert opinions.

Project actions

01Clearly define your decision criteria and ensure they are measurable or rankable.
02Consider using MCDA tools to structure your decision-making process, especially when dealing with multiple factors.

Method & Evidence

AimTo develop and apply a hybrid decision-making model for determining the optimal locations of parcel pick-up points in an urban environment.

MethodHybrid Multi-Criteria Decision Analysis (MCDA) using Spherical Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).

ProcedureCriteria for location selection were identified through literature review and expert consultation. The Spherical Fuzzy AHP was used to determine the weights of these criteria based on expert opinions. Subsequently, the TOPSIS method was applied to rank potential locations using the weighted criteria.

ContextUrban logistics and e-commerce last-mile delivery.

Variables

IVCriteria for location selection (e.g., accessibility, proximity to population, traffic density).

DVRanked order of optimal locations for parcel pick-up points.

CVGeographical area (Istanbul), type of service (parcel pick-up points), specific MCDA methods used (Spherical Fuzzy AHP, TOPSIS).

Strengths & Limitations

Strengths

+Utilizes a novel hybrid MCDA approach, combining the strengths of AHP and TOPSIS.
+Incorporates fuzzy logic to handle uncertainty and subjective expert opinions.

Limitations

The model relies heavily on the quality and availability of data, and expert opinions can be subjective. The complexity of the model might be challenging to implement without specialized software.

Reliability & validity

Reliability could be assessed by re-running the model with the same data to see if the rankings remain consistent. Validity is supported by the use of established MCDA techniques and expert input, but could be further strengthened by comparing the model's predictions with actual usage data of pick-up points.

Think critically

How might the weighting of criteria change if the primary goal shifts from customer convenience to operational cost reduction?

Design Principles

"Utilize hybrid MCDA models for complex location-based decision-making, integrating qualitative and quantitative data with expert input."

This research provides a structured, data-driven approach to a critical logistical challenge in e-commerce. By developing and applying a robust decision-making model, designers and logistics professionals can move beyond intuition to strategically place infrastructure that enhances efficiency and user convenience.

What This Means for Your Design

This study shows how to use a smart computer model that combines different math ideas (AHP and TOPSIS) to figure out the best places to put parcel pick-up spots in a city.

How to use in your project

1.Reference this study when discussing the methodology for selecting optimal locations for a product or service, particularly if using MCDA techniques.

Add to My Project

Quick Cite

Paragraph starter

This research provides a robust framework for location selection, employing a hybrid Spherical Fuzzy AHP-TOPSIS model to systematically evaluate multiple criteria. The methodology, which integrates expert judgment with fuzzy logic, offers a sophisticated approach to optimizing the placement of essential services like parcel pick-up points within urban environments, a process directly applicable to strategic design decisions in logistics and service provision.

Source

International Journal of the Analytic Hierarchy Process

IDEAL LOCATION SELECTION FOR CONTACTLESS PARCEL PICK-UP POINTS

journal · 2023

View source

Questions About This Research

What does the research say about hybrid ahp-topsis model optimizes parcel pick-up point locations?: When selecting critical infrastructure locations, employ hybrid MCDA models that incorporate expert judgment and fuzzy logic to systematically evaluate multiple, potentially conflicting criteria. Evidence: International Journal of the Analytic Hierarchy Process (2023).
Why does "Hybrid AHP-TOPSIS Model Optimizes Parcel Pick-Up Point Locations" matter for design?: This research provides a structured, data-driven approach to a critical logistical challenge in e-commerce. By developing and applying a robust decision-making model, designers and logistics professionals can move beyond intuition to strategically place infrastructure that enhances efficiency and user convenience.
How can designers apply this research?: When selecting critical infrastructure locations, employ hybrid MCDA models that incorporate expert judgment and fuzzy logic to systematically evaluate multiple, potentially conflicting criteria.
What were the main findings?: The hybrid Spherical Fuzzy AHP-TOPSIS model successfully ranked potential parcel pick-up point locations.. Kadikoy, Umraniye, and Atasehir were identified as the most ideal locations in Istanbul based on the applied criteria.
What research method was used?: Hybrid Multi-Criteria Decision Analysis (MCDA) using Spherical Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)..
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2023 journal from International Journal of the Analytic Hierarchy Process.
What should I do differently in my next project?: Adapt the Spherical Fuzzy AHP-TOPSIS framework to identify optimal locations for new service points, distribution centres, or retail stores by defining relevant criteria and gathering expert opinions.
What are the limitations?: The model's applicability is specific to the chosen criteria and the urban context of Istanbul; adaptation is needed for different geographical or logistical scenarios. The subjective nature of expert input can introduce bias.