Bi-objective design of household E-waste collection with public advertising and competition from informal sectors.

The rapid expansion of technology, coupled with the falling prices of electronic products and their fast obsolescence, has resulted in a rapidly-growing amount of e-waste worldwide. Because of adverse effects on environment and public health, more and more countries and regions have begun to establish and operate public e-waste collection systems. In many developing countries, the low level of environmental awareness and the existence of informal sectors present obstacles to the success of such collection systems. This paper proposes to design a household e-waste collection network and launch a corresponding public service advertising campaign to counteract the informal recycling markets. The proposed mixed integer nonlinear program maximizes the amount of collected e-waste and minimizes overall costs of developing the network and its advertising campaign. A decomposition-based, multi-objective metaheuristic was developed to obtain the Pareto frontier. A case study based on the e-waste collection system in Changsha, China contextualizes the problem and developed methodology. Experiment results show that the cost of network construction and public advertising must be carefully balanced for limited budgets. The impact of residents' environmental awareness is also important to the collection effect. From a methodology perspective, this paper uses the Pareto analysis approach to study the design of household e-waste collection networks, with a supporting public service announcement campaign, in the presence of informal recycling markets. This paper also offers a policy design decision support tool to help regulators determine most workable policies that will balance the trade-offs between the two objectives.

A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle.

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0-1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25-200 targets, 12-80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.

Reliable Facility Location Problem with Facility Protection.

This paper studies a reliable facility location problem with facility protection that aims to hedge against random facility disruptions by both strategically protecting some facilities and using backup facilities for the demands. An Integer Programming model is proposed for this problem, in which the failure probabilities of facilities are site-specific. A solution approach combining Lagrangian Relaxation and local search is proposed and is demonstrated to be both effective and efficient based on computational experiments on random numerical examples with 49, 88, 150 and 263 nodes in the network. A real case study for a 100-city network in Hunan province, China, is presented, based on which the properties of the model are discussed and some managerial insights are analyzed.

Correlation between weighted spectral distribution and average path length in evolving networks.

The weighted spectral distribution (WSD) is a metric defined on the normalized Laplacian spectrum. In this study, synchronic random graphs are first used to rigorously analyze the metric's scaling feature, which indicates that the metric grows sublinearly as the network size increases, and the metric's scaling feature is demonstrated to be common in networks with Gaussian, exponential, and power-law degree distributions. Furthermore, a deterministic model of diachronic graphs is developed to illustrate the correlation between the slope coefficient of the metric's asymptotic line and the average path length, and the similarities and differences between synchronic and diachronic random graphs are investigated to better understand the correlation. Finally, numerical analysis is presented based on simulated and real-world data of evolving networks, which shows that the ratio of the WSD to the network size is a good indicator of the average path length.

K-Shortest-Path-Based Evacuation Routing with Police Resource Allocation in City Transportation Networks.

Emergency evacuation aims to transport people from dangerous places to safe shelters as quickly as possible. Police play an important role in the evacuation process, as they can handle traffic accidents immediately and help people move smoothly on roads. This paper investigates an evacuation routing problem that involves police resource allocation. We propose a novel k-th-shortest-path-based technique that uses explicit congestion control to optimize evacuation routing and police resource allocation. A nonlinear mixed-integer programming model is presented to formulate the problem. The model's objective is to minimize the overall evacuation clearance time. Two algorithms are given to solve the problem. The first one linearizes the original model and solves the linearized problem with CPLEX. The second one is a heuristic algorithm that uses a police resource utilization efficiency index to directly solve the original model. This police resource utilization efficiency index significantly aids in the evaluation of road links from an evacuation throughput perspective. The proposed algorithms are tested with a number of examples based on real data from cities of different sizes. The computational results show that the police resource utilization efficiency index is very helpful in finding near-optimal solutions. Additionally, comparing the performance of the heuristic algorithm and the linearization method by using randomly generated examples indicates that the efficiency of the heuristic algorithm is superior.