ASIF Approach to Solve the Green Traveling Salesman Problem

Introduction

There is an important need for greening everyday life activities in many regions of the world. Middle-East and north-Africa (MENA) cities are nowadays subject (through industrialization) to both economic and demographic growth and are therefore in a need for greener transportation systems to be available (Banister, 2012). Many organizations in this region are ready to demonstrate high commitment in going green. But face difficulties in accessing the right tools, methods, and technologies that permit to maintain a low ecological footprint while reaching high revenues.

Greener mobility and accessibility are imperative elements for economy and welfare in MENA cities. Urban areas can display a huge amount of transportation-related problems ranging from traffic congestion to health issues and economic charges (Zeimpekis, Minis, Giaglis, & Mamassis, 2013). Both citizen and companies need to commute and transport goods locally and regionally using the fastest, cost-effective and greener way (Lewczuk, Żak, Pyza, & Jacyna-Gołda, 2013). Sustainable transport and green logistics try to provide a set of combined solutions to meet these objectives.

The present work addresses this problem in the case of the city of Casablanca; the urban area of the city presents an interesting use case for solving transportation problems. The city has an urban area of 386Km² and a metropolitan area of 1615Km² (Rhinane, Hilali, Bahi, & Berrada, 2012) it is economically and demographically the largest city in Morocco. Historical, Social and economic considerations give the city high traffic flows and continuously evolving transportation limitations (Brejon De Lavergnee, 1986; Joly, 1948).

Morocco is an emerging economy, and one of the strongest and fast growing in Middle East and Africa, facilitating a greener economy using cleaner transportation systems, and cleaner manufacturing processes is of a high priority to the Moroccan Government. There are many initiatives and regulations but the most noticeable one in the field of transportation is the latest implementation of a sustainable, nature friendly and efficient tramway network in the city of Casablanca that commutes over 80.000 citizens daily using cleaner energy (Gillette, 2013).

However other mobility driven -and also goods delivery- factors maintain a huge demand for fossil-fuel based modes like cars, taxis, buses, trucks and intercity buses. In this particular case, the government has switched to a more technological aspect in reducing the emissions and facilitating a greener transportation system, the new regulations advocate upgrading one class of taxis in Morocco to more recent vehicles with efficient engines and fewer emissions. This shift will be discussed in detail within this work.

However, these regulations and mitigation policies are intricate to implement, expenses in time and resources to study the dynamics that lead to a certain volume of emissions, to take decisions by policy makers, and finally offices and procedures to implement them. Plus, change management routines and post implementation control. We want in the scope of this work, to offer an effortless alternative to mitigate emissions and energy consumption in the current transportation architecture without changing any technological aspect or dictating any new regulation. This will be done through optimization of transportation itineraries using green objectives in the most recurrent transportation problem.

A frequent problem in transportation science is the traveling salesman problem (TSP). This problem consists of finding the minimal closed-tour passing by a set of locations (Punnen, 2007). Both citizens and businesses are facing real-world forms of this problem every day. Delivering goods to a number of customers, or accessing some regular services while commuting from work to home are examples of real world applications of the TSP. Small to medium instances of this problem can be efficiently approximated using modern metaheuristics like the one we are using in this paper. Ant colony optimization and other metaheuristics have demonstrated robustness and efficiency in handling combinatorial problems like the TSP and other routing problems (Dorigo, Maniezzo, & Colorni, 1996; Layeb, 2015).