Network Design Model with Evacuation Constraints Under Uncertainty

Abstract: Nepal earthquake, have shown the need for quick response evacuation and assistance routes. Evacuation routes are, mostly, based on the capacities of the roads network. However, in extreme cases, such as earthquakes, roads network infrastructure may adversely affected, and may not supply their required capacities. If for various situations, the potential damage for critical roads can be identify in advance, it is possible to develop an evacuation model, that can be used in various situations to plan the network structure in order to provide fast and safe evacuation. This paper focuses on the development of a model for the design of an optimal evacuation network which simultaneously minimizes construction costs and evacuation time. The model takes into consideration infrastructures vulnerability (as a stochastic function which is dependent on the event location and magnitude), road network, transportation demand and evacuation areas. The paper presents a mathematic model for the presented problem. However, since an optimal solution cannot be found within a reasonable timeframe, a heuristic model is presented as well. The heuristic model is based on evolutionary algorithms, which also provides a mechanism for solving the problem as a stochastic and multi-objective problem

Stochastic Multi-Objective Evacuation Model Under Managed and Unmanaged policies

Abstract Natural and man-created disasters, such as hurricanes, earthquakes, tsunamis, accidents and terrorist attacks, require evacuation and assistance routes. Evacuation routes are mostly based on the capacities of the road network. However, in extreme cases, such as earthquakes, road network infrastructure may adversely be affected, and may not supply their required capacities. If for various situations, the potential damage for critical roads can be identified in advance, it is possible to develop an evacuation model, that can be used in various situations. This paper focuses on the development of a model for the design of an optimal evacuation network which simultaneously minimizes retrofit costs of critical links (bridges, tunnels, etc.) and evacuation time. The model considers infrastructures' vulnerability (as a stochastic function which is dependent on the event location and magnitude), road network, transportation demand and evacuation areas. Furthermore, the model evaluates the benefits of managed evacuation (system optimum) when compared to unmanaged evacuation (user equilibrium). The paper presents a mathematic model for the presented problem. However, since an optimal solution cannot be found within a reasonable timeframe, a heuristic model is presented as well. This heuristic model is based on evolutionary algorithms, which also provides a mechanism for solving the problem as a multi-objective stochastic problem. Using a real-world data, the algorithm is evaluated and compared to the unmanaged evacuation conditions. The results clearly demonstrate the advantages of managed evacuation, as the average travel time can be reduced by 5% to 30%

Urban bus network of priority lanes: A combined multi-objective, multi-criteria and group decision-making approach

This study presents a multi-objective approach for selecting an optimal network of public transport (PT) priority lanes. Bus priority schemes and techniques on urban roads and highways have proven effective for increasing reliability, efficiency, and faster travel times. This study develops a multi-objective model for selecting an optimal PT priority lanes network that 1) maximizes total travel time savings; 2) maintains balanced origin and destination terminals; and 3) minimizes the construction budget. In contrast to commonly used single objective models, which must be executed numerous times in order to provide the decision-maker with feasible solutions, multi-objective models exhibit a complete set of feasible and optimal solutions with a single execution. Since the major disadvantage of a multi-objective model is the need to select a preferred solution from a set, a multi-criteria approach was developed for: 1) ranking each decision-maker\u27s solutions; and 2) selecting a compromise solution acceptable to a group of decision-makers. This methodology is demonstrated with a case study of Petah Tikva, a medium-sized city in Israel

Multi-Objective Optimal Allocation of Wireless Bus Charging Stations Considering Costs and the Environmental Impact

In recent years, due to environmental concerns, there has been an increasing desire to develop alternative solutions to traditional energy sources. Since transportation is a significant fossil-fuel consumer, the development of electric vehicles, especially buses, has the potential to reduce fossil-fuel use and thus provide a better living environment. The aim of the current work was to develop an optimal allocation model for designing a system-wide network of wireless bus charging stations. The main advantages of wireless charging are the need for a much smaller battery and the fact that the charging process may occur under both static and dynamic (in-motion) conditions. The suggested approach consisted of a multi-objective model that selected the locations for the charging stations while (a) minimizing the costs, (b) maximizing the environmental benefit, and (c) minimizing the number of charging stations. The problem was formulated as a multi-objective non-linear optimization model with both deterministic and stochastic variations. An efficient genetic algorithm was introduced to solve the problem. A test case was used to demonstrate the model; accordingly, the decision-maker was provided with a solution set from which the best fit solution could be selected

Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance

We introduce the Cooperative Multi-Agent Path Finding (Co-MAPF) problem, an extension to the classical MAPF problem, where cooperative behavior is incorporated. In this setting, a group of autonomous agents operate in a shared environment and have to complete cooperative tasks while avoiding collisions with the other agents in the group. This extension naturally models many real-world applications, where groups of agents are required to collaborate in order to complete a given task. To this end, we formalize the Co-MAPF problem and introduce Cooperative Conflict-Based Search (Co-CBS), a CBS-based algorithm for solving the problem optimally for a wide set of Co-MAPF problems. Co-CBS uses a cooperation-planning module integrated into CBS such that cooperation planning is decoupled from path planning. Finally, we present empirical results on several MAPF benchmarks demonstrating our algorithm’s properties

Study on the dynamic properties of AM-SLM AlSi10Mg alloy using the Split Hopkinson Pressure Bar (SHPB) technique

Additive manufacturing by Selective Laser Melting of metals is attracting substantial attention, due to its advantages, such as short-time production of customized structures. This technique is useful for building complex components using a metallic pre-alloyed powder. One of the most used materials in AMSLM is AlSi10Mg powder. Additively manufactured AlSi10Mg may be used as a structural material and it static mechanical properties were widely investigated. Properties in the strain rates of 5×102–1.6×103 s-1 and at higher strain rates of 5×103 –105 s-1 have been also reported. The aim of this study is investigation of dynamic properties in the 7×102–8×103 s-1 strain rate range, using the split Hopkinson pressure bar technique. It was found that the dynamic properties at strain-rates of 1×103–3×103 s-1 depend on a build direction and affected by heat treatment. At higher and lower strain-rates the effect of build direction is limited. The anisotropic nature of the material was determined by the ellipticity of samples after the SHPB test. No strain rate sensitivity was observed

A Multi-Objective Genetic Algorithm for Outlier Removal

Quantitative structure activity relationship (QSAR) or quantitative structure property relationship (QSPR) models are developed to correlate activities for sets of compounds with their structure-derived descriptors by means of mathematical models. The presence of outliers, namely, compounds that differ in some respect from the rest of the data set, compromise the ability of statistical methods to derive QSAR models with good prediction statistics. Hence, outliers should be removed from data sets prior to model derivation. Here we present a new multi-objective genetic algorithm for the identification and removal of outliers based on the <i>k</i> nearest neighbors (<i>k</i>NN) method. The algorithm was used to remove outliers from three different data sets of pharmaceutical interest (logBBB, factor 7 inhibitors, and dihydrofolate reductase inhibitors), and its performances were compared with those of five other methods for outlier removal. The results suggest that the new algorithm provides filtered data sets that (1) better maintain the internal diversity of the parent data sets and (2) give rise to QSAR models with much better prediction statistics. Equally good filtered data sets in terms of these metrics were obtained when another objective function was added to the algorithm (termed “preservation”), forcing it to remove certain compounds with low probability only. This option is highly useful when specific compounds should be preferably kept in the final data set either because they have favorable activities or because they represent interesting molecular scaffolds. We expect this new algorithm to be useful in future QSAR applications

Study on the dynamic properties of AM-SLM AlSi10Mg alloy using the Split Hopkinson Pressure Bar (SHPB) technique

Additive manufacturing by Selective Laser Melting of metals is attracting substantial attention, due to its advantages, such as short-time production of customized structures. This technique is useful for building complex components using a metallic pre-alloyed powder. One of the most used materials in AMSLM is AlSi10Mg powder. Additively manufactured AlSi10Mg may be used as a structural material and it static mechanical properties were widely investigated. Properties in the strain rates of 5×102–1.6×103 s-1 and at higher strain rates of 5×103 –105 s-1 have been also reported. The aim of this study is investigation of dynamic properties in the 7×102–8×103 s-1 strain rate range, using the split Hopkinson pressure bar technique. It was found that the dynamic properties at strain-rates of 1×103–3×103 s-1 depend on a build direction and affected by heat treatment. At higher and lower strain-rates the effect of build direction is limited. The anisotropic nature of the material was determined by the ellipticity of samples after the SHPB test. No strain rate sensitivity was observed