Abstract
Nowadays, online route planners for soft modes are provided by several platforms such as Google Maps, OpenStreetMap, Here, or Waze. Itineraries are usually built using Shortest Path Problem algorithms that minimize the travel time or distance. In this work, we aim to identify and quantify the main features that influence itineraries’ choice by soft modes users in urban areas, able to support multi-objective routing, using simulated scenarios. We propose a set of 21 indicators, grouped into five dimensions: Safety-Security, Comfort, Air Quality, Accessibility and Time-Distance. Another contribution of this work is the simulation of scenarios to study soft modes’ multi-objective routing within urban areas.

Abstract
The rising number of people living in city centers is connected to an increase of private vehicles, traffic, and associated harmful effects. Efforts have been made to promote a modal shift to the use of more sustainable transportation means, such as walking and cycling, but several factors hinged to safety, comfort, and accessibility, still hinder this goal. Current route planners often focus on two particular dimensions, time and distance, which might not be enough to support other personal perceptions. We need to consider new aspects and different dimensions, such as air quality, noise levels, or people density, fueled by the recent advances in the area of sensorization and the Internet of Things. We tested the idea of an innovative route planner with surveys and focus groups and concluded that there is an interest for more power to customize personal routes, which could be a key element boosting soft mode mobility.

Abstract
This paper presents a study on the complexity of cargo arrangements in the pallet loading problem. Due to the diversity of perspectives that have been presented in the literature, complexity is one of the least studied practical constraints. In this work, we aim to refine and propose a new set of metrics to measure the complexity of an arrangement of cargo in a pallet. The parameters are validated using statistical methods, such as principal component analysis and multiple linear regression, using data retrieved from the company logistics. Our tests show that the number of boxes was the main variable responsible for explaining complexity in the pallet loading problem.

Abstract
In the Physical Internet supply chain paradigm, modular boxes are one of the main drivers. The dimension of the modular boxes has already been subject to some studies. However, the usage of a modular approach on the container loading problem has not been accessed. In thiswork, we aim to assess the impact of modular boxes in the context of the Physical Internet on the optimization of loading solutions. A mathematical model for the CLP problem is used, and extensive computational experimentswere performed in a set of problem instances generated considering the Physical Internet concept. From this study, it was possible to conclude for the used instances that modular boxes contribute to a higher volume usage and lower computational times.

Abstract
The integration of the outbound and the inbound logistics of a company leads to a large transportation network, allowing to detect backhauling opportunities to increase the efficiency of the transportation. In collaborative networks, backhauling is used to find profitable services in the return trip to the depot and to reduce empty running of vehicles. This work investigates the vertical collaboration between a shipper and a carrier for the planning of integrated inbound and outbound transportation. Based on the hierarchical nature of the relation between the shipper and the carrier and their different goals, the problem is formulated as a bilevel Vehicle Routing Problem with Selective Backhauls (VRPSB). At the upper level, the shipper decides the minimum cost delivery routes and the set of incentives offered to the carrier to perform integrated routes. At the lower level, the carrier decides which incentives are accepted and on which routes the backhaul customers are visited. We devise a mathematical programming formulation for the bilevel VRPSB, where the routing and the pricing problems are optimized simultaneously, and propose an equivalent reformulation to reduce the problem to a single-level VRPSB. The impact of collaboration is evaluated against non-collaborative approaches and two different side payment schemes. The results suggest that our bilevel approach leads to solutions with higher synergy values than the approaches with side payments.

Abstract
The backroom of retail stores has structural differences when compared with other warehouses and distribution centres, which are more traditionally studied in the literature. This paper presents a mathematical optimisation approach for an unequal area facility layout problem, applied in designing the backroom layout in grocery retail. A set of rectangular facilities (backroom departments) with given area requirements has to be placed, without overlapping, on a limited floor space (backroom area), which can have a regular or an irregular shape. The objective is to find the location and format of the storage departments, such that the walking distances in the store by store employees are minimised. The proposed approach is tested in a European grocery retailer. In the computational experiments, several real store layouts are compared with the ones suggested by the proposed model. The decrease in the walking distances is, on average, 30 percent. In order to understand what the current designers' strategy is, a set of scenarios was created and compared with the real layouts. Each scenario ignores a characteristic of the problem. The goal is to understand what aspect designers are currently discarding. The findings indicate that, currently, designers neglect the different replenishment frequencies of storage departments.