Split Demand Research Articles

Highly active nonprecious metal hydrogen evolution electrocatalyst: ultrafine molybdenum carbide nanoparticles embedded into a 3D nitrogen-implanted carbon matrix

The generation of clean and sustainable hydrogen fuel through water splitting demands efficient and robust earth-abundant catalysts for the hydrogen evolution reaction (HER). A new hybrid, which was fabricated by incorporating molybdenum carbide (MoxC) nanoparticles into a nitrogen-implanted three-dimensional carbon matrix (MoCN-3D), was developed as a highly active and durable nonprecious metal electrocatalyst for HER. The porous architecture of MoCN-3D can provide continuous mass transportation with a minimal diffusion resistance and thus produce effective electrocatalytic kinetics in both acidic and alkaline media. Experimental observations in combination with density functional theory calculations reveal that the effective coupling between molybdenum carbide nanoparticles and the carbon matrix, as well as N hybrid coordination, can modify the electronic Fermi level of the final hybrid, which synergistically reduces the proton adsorption and the reduction barrier during electrocatalytic HER. A three-dimensional, porous catalytic framework makes it easier to flow water past active sites that turn this molecule into hydrogen. The hunt for cheaper alternatives to platinum catalysts for water splitting led Jinhua Ye from Tianjin University in China and co-workers to investigate molybdenum carbide (Mo2C). These catalysts show significant hydrogen evolution when confined to nanoscale shapes. The researchers enhanced this behaviour by replacing imidazole-zinc units in a zeolite-type metal organic framework with molybdenum. Heating at high temperature turned the sieve-like template into a new composite containing ultrafine Mo2C nanoparticles and a three-dimensional matrix of graphitic carbon implanted with nitrogen atoms. The physical structure of this material improves mass transport of reagents to and from catalytic surface sites, while favorable interactions between Mo2C and the carbon matrix lower energy barriers needed to slice water apart. A new hybrid, fabricated by incorporating molybdenum carbide (Mo2C) nanoparticles into nitrogen-implanted three-dimensional carbon matrix (MoCN-3D), has been developed as a highly active and durable nonprecious metal electrocatalyst for HER. The porous architecture of the developed catalyst MoCN-3D can provide continuous mass transportation with a minimal diffusion resistance and thus produce effective electrocatalytic kinetics in both acidic and alkaline media.

Efficient hydrogen evolution catalysis using ternary pyrite-type cobalt phosphosulphide.

The scalable and sustainable production of hydrogen fuel through water splitting demands efficient and robust Earth-abundant catalysts for the hydrogen evolution reaction (HER). Building on promising metal compounds with high HER catalytic activity, such as pyrite structure cobalt disulphide (CoS2), and substituting non-metal elements to tune the hydrogen adsorption free energy could lead to further improvements in catalytic activity. Here we present a combined theoretical and experimental study to establish ternary pyrite-type cobalt phosphosulphide (CoPS) as a high-performance Earth-abundant catalyst for electrochemical and photoelectrochemical hydrogen production. Nanostructured CoPS electrodes achieved a geometrical catalytic current density of 10 mA cm(-2) at overpotentials as low as 48 mV, with outstanding long-term operational stability. Integrated photocathodes of CoPS on n(+)-p-p(+) silicon micropyramids achieved photocurrents up to 35 mA cm(-2) at 0 V versus the reversible hydrogen electrode (RHE), onset photovoltages as high as 450 mV versus RHE, and the most efficient solar-driven hydrogen generation from Earth-abundant systems.

The split-demand one-commodity pickup-and-delivery travelling salesman problem

This paper introduces a new vehicle routing problem transferring one commodity between customers with a capacitated vehicle that can visit a customer more than once, although a maximum number of visits must be respected. It generalizes the capacitated vehicle routing problem with split demands and some other variants recently addressed in the literature. We model the problem with a single commodity flow formulation and design a branch-and-cut approach to solve it. We make use of Benders Decomposition to project out the flow variables from the formulation. Inequalities to strengthen the linear programming relaxation are also presented and separated within the approach. Extensive computational results illustrate the performance of the approach on benchmark instances from the literature.

A genetic algorithm for dynamic inbound ordering and outbound dispatching problem with delivery time windows

This article considers an inbound ordering and outbound dispatching problem for a single product in a third-party warehouse, where the demands are dynamic over a discrete and finite time horizon, and moreover, each demand has a time window in which it must be satisfied. Replenishing orders are shipped in containers and the freight cost is proportional to the number of containers used. The problem is classified into two cases, i.e. non-split demand case and split demand case, and a mathematical model for each case is presented. An in-depth analysis of the models shows that they are very complicated and difficult to find optimal solutions as the problem size becomes large. Therefore, genetic algorithm (GA) based heuristic approaches are designed to solve the problems in a reasonable time. To validate and evaluate the algorithms, finally, some computational experiments are conducted.

Heuristics for routes generation in pickup and delivery problem

In shipping services, the goal is to propose cyclical routes which ensure transport of required goods among the main centers of the regions. It is classified as a pickup and delivery problem with split demand and reloading. The objective is to minimize total shipping costs, or the total length of all cyclical routes. The optimum solution gives a number of vehicles going on arcs of the communication network and the amount of goods being transported on the arcs. Consequently, cyclical routes and depots are proposed for all vehicles. First, the multi-graph, in which each directed arc corresponds to exactly one vehicle, is generated. The multi-graph satisfies the condition that the number of arcs entering each node equals the number of arcs exiting the node. The heuristic method of loading goods onto a vehicle in the pickup node and to transport it to the delivery node without reloading onto another vehicle is proposed. The method is verified in the case study carried out on the DHL company.

Integrated use of fuzzy c-means and convex programming for capacitated multi-facility location problem

In this study a fuzzy c-means clustering algorithm based method is proposed for solving a capacitated multi-facility location problem of known demand points which are served from capacitated supply centres. It involves the integrated use of fuzzy c-means and convex programming. In fuzzy c-means, data points are allowed to belong to several clusters with different degrees of membership. This feature is used here to split demands between supply centers. The cluster number is determined by an incremental method that starts with two and designated when capacity of each cluster is sufficient for its demand. Finally, each group of cluster and each model are solved as a single facility location problem. Then each single facility location problem given by fuzzy c-means is solved by convex programming which optimizes transportation cost is used to fine-tune the facility location. Proposed method is applied to several facility location problems from OR library (Osman & Christofides, 1994) and compared with centre of gravity and particle swarm optimization based algorithms. Numerical results of an asphalt producer's real-world data in Turkey are reported. Numerical results show that the proposed approach performs better than using original fuzzy c-means, integrated use of fuzzy c-means and center of gravity methods in terms of transportation costs.

A tabu search with vocabulary building approach for the vehicle routing problem with split demands

In the vehicle routing problem (VRP) a fleet of vehicles with limited capacity is utilised to supply the demand of a set of customers located around a unique depot while minimising the total travelled distance. All customer demands are supplied and customers are visited by exactly one vehicle. In the split delivery vehicle routing problem (SDVRP), customers can be visited by more than one vehicle meaning their demands can be split among multiple vehicles. This paper presents a learning procedure, called tabu search with vocabulary building approach (TSVBA) for solving the SDVRP. TSVBA is a population-based search approach that uses a set of solutions to find attractive solution attributes with which to construct new solutions. As the search progresses, the solution set evolves; better solutions move into the set while bad solutions are removed. The proposed learning procedure was tested on benchmark instances and performed well when its solutions are compared to those reported in the literature. New best solutions are obtained on some benchmark problems available.

An extension of the relaxation algorithm for solving a special case of capacitated arc routing problems

In this paper, we propose an exact method for solving a special integer program associated with the classical capacitated arc routing problems (CARPs) called split demand arc routing problems (SDARP). This method is developed in the context of monotropic programming theory and bases a promising foundation for developing specialized algorithms in order to solve general integer programming problems. In particular, the proposed algorithm generalizes the relaxation algorithm developed by Tseng and Bertsekas (Math. Oper. Res. 12(4):569–596, 1987) for solving linear programming problems. This method can also be viewed as an alternative for the subgradient method for solving Lagrangian relaxed problems. Computational experiments show its high potential in terms of efficiency and goodness of solutions on standard test problems.

Integrated business agents for processing free text information

The Internet functions as an increasingly important channel for retailing commerce and business transactions. Although nearly five billion web sites exist on die World Wide Web, an integrated mediator, called a business agent. is sought to negotiate between suppliers and buyers Such an intelligent business broker is thus necessary to support efficient and effective sharing of information This work proposes an entirely new business agent architecture comprised of five elements, namely Business Spy Agent, Supply and Demand Analysis, Supply and Demand Classification, Matching and Negotiation, and Hidden Business Mining. The proposed architecture encompasses four trading processes, including supply and demand identification, product brokering, merchant brokering and negotiation. The architecture introduces the notion of ontology to increase the precision of classification and more the effectiveness of negotiation. Experiments involving die proposed business agent show a significant successful pairing rate of 82% among suppliers and buyers. Simulation results indicate that die options, including Negotiable. Designated Brand and Split Demand, affect the match ratio differently from various perspectives.

Routing helicopters for crew exchanges on off-shore locations

This paper deals with a vehicle routing problem with split demands, namely the problem of determining a flight schedule for helicopters to off-shore platform locations for exchanging crew people employed on these platforms. The problem is formulated as an LP model and solved by means of a column-generation technique including solving TSP problems. Since the final solution needs to be integral, we have chosen a rounding procedure to obtain an integer solution. Since the LP approach needs a considerable amount of computer time, it is only suitable for long-term planning practices. For the usual short-term planning, we have designed the so-called Cluster-and-Route Heuristic together with a number of improvement heuristics. The Cluster-and-Route procedure constructs a suitable clustering of the platforms and simultaneously forms the routes of the helicopter flights associated with the clusters. This approach is different from the usual heuristics, in which the clusters are constructed first, and the routes for each cluster are made afterwards. Simulations with various data sets show that the new heuristic outperforms the usual heuristics for vehicle routing problems. Even better results are obtained when improvement heuristics are applied. We use four improvement heuristics, including, so-called 1-opt and 2-opt procedures.