Alternative-fuel station network design under impact of station failures

In this paper, we have formulated a mixed-integer non-linear programming model for alternative-fuel station location problem in which each station can fail with a site-specific probability. The model aims to maximise the total expected traffic volume that can be refuelled by the unreliable alternative-fuel stations. Based on the linearisation techniques, i.e., probability chains and piecewise-linear functions, we linearise the non-linearity of compound probability terms in the non-linear model to solve this problem efficiently. An efficient Tabu search algorithm is also developed to solve the large-size instances. In addition, we extend the model to deal with reliable multi-period alternative-fuel station network design. Computational experiments, carried out on the well-known benchmark instances where the probability of station failures is uniformly generated, show that the proposed models and algorithm can obtain the optimal solutions within a reasonable computation time. Compared to a standard station location model that disregards the potential for station failures, our model designs more reliable alternative-fuel station network under risk of station failures. A sensitivity analysis of failure probabilities in the station network design is investigated to demonstrate the robustness of our model and study how variability in the probability of station failure affects solution robustness

Minimizing total cost of home energy consumption under uncertainties

long with the development of renewable energy sources, energy storage units are introduced to increase the stability and reliability of electricity production. The storage units can improve the efficiency of energy consumption for consumers as well. By smartly controlling home appliances, renewable energy sources and energy storage units, consumers can satisfy their energy demand with a minimum cost. However, the declined maximum capacity of energy storage units and the unstable power of electricity grid, due to randomly unexpected failures, can cause challenges for consumers’ energy plans. In this article, we develop a novel joint chance-constraint mixed-integer linear programming model to support consumers in finding the optimal energy plans for a minimum cost of energy consumption under the simultaneous impact of unexpected failures on energy storage units and electricity grid. A case study for a set of households in Nottingham, United Kingdom, is used to demonstrate the efficiency of the proposed model. Some interesting insights are achieved for home energy management under uncertainties

Multifactorial Evolutionary Algorithm For Clustered Minimum Routing Cost Problem

Minimum Routing Cost Clustered Tree Problem (CluMRCT) is applied in various fields in both theory and application. Because the CluMRCT is NP-Hard, the approximate approaches are suitable to find the solution for this problem. Recently, Multifactorial Evolutionary Algorithm (MFEA) has emerged as one of the most efficient approximation algorithms to deal with many different kinds of problems. Therefore, this paper studies to apply MFEA for solving CluMRCT problems. In the proposed MFEA, we focus on crossover and mutation operators which create a valid solution of CluMRCT problem in two levels: first level constructs spanning trees for graphs in clusters while the second level builds a spanning tree for connecting among clusters. To reduce the consuming resources, we will also introduce a new method of calculating the cost of CluMRCT solution. The proposed algorithm is experimented on numerous types of datasets. The experimental results demonstrate the effectiveness of the proposed algorithm, partially on large instance

Models and Heuristics for the Flow-Refuelling Location Problem

Purpose of this paper: Firstly, the paper serves as an overview of the emerging field of flow-refuelling location, which mainly occurs in the context of locating alternative-fuel (hydrogen, electric, liquefied natural gas and hybrid) vehicle refuelling stations. We aim to review and explain models and solution approaches, with a particular focus on mathematical programming formulations. Secondly, we propose a new heuristic for this problem and investigate its performance. Design/methodology/approach: The subject scope of this paper is the flow-refuelling location model (FRLM). While in most location problems demand arises at customer locations, in so-called flow-capturing models it is associated with journeys (origin-destination pairs). What makes the FRLM even more challenging is that due to the limited driving range of alternative-fuel vehicles, more than one facility may be required to satisfy the demand of a journey. There are currently very few such refuelling stations, but ambitious plans exist for massive development – making this an especially ripe time for researchers to investigate this problem. There already exists a body of work on this problem; however different authors make different model assumptions, making comparison difficult. For example, in some models facilities must lie on the shortest route from origin to destination, while in others detours are allowed. We aim to highlight difference in models in our review. Our proposed methodology is built on the idea of solving the relaxation of the mixed-integer linear programming formulation of the problem, identifying promising variables, fixing their values and solving the resulting (so-called restricted) problems optimally. It is somewhat similar to Kernel Search which has recently gained popularity. We also use a parallel computing strategy to simultaneously solve a number of restricted problems with less computation effort for large-sized instances. Findings: Our experimental results show that the proposed heuristic can find optimal solutions in a reasonable amount of time, outperforming other heuristics from the literature. Value: We believe the paper is of value to both academics and practitioners. The review should help researchers new to this field to orient themselves in the maze of different problem versions, while helping practitioners identify models and approaches applicable to their particular problem. The heuristic proposed can be directly used by practitioners; we hope it will spark further works on this area of logistics but also on other optimisation problems where Kernel Search type methods can be applied. Research limitations: This being the first paper applying a restricted-subproblem approach to this problem it is necessarily limited in scope. Applying a traditional Kernel Search method would be an interesting next step. The proposed heuristic should also be extended to cover for more than just one FRLM model: certainly the capacitated FRLM, the FRLM with deviation, the fixed-charge FRLM and the multi-period FRLM should be investigated. Practical implications: Our work adds to a body of research that can inform decisionmakers at governmental or international level on strategic decisions relating to the establishment or development of alternative-fuel refuelling station networks

An efficient heuristic algorithm for the alternative-fuel station location problem

We have developed an efficient heuristic algorithm for location of alternative-fuel stations. The algorithm is constructed based on solving the sequence of subproblems restricted on a set of promising station candidates, and fixing a number of the best promising station locations. The set of candidates is initially determined by solving a relaxation model, and then modified by exchanging some stations between the promising candidate set and the remaining station set. A number of the best station candidates in the promising candidate set can be fixed to improve computation time. In addition, a parallel computing strategy is integrated into solving simultaneously the set of subproblems to speed up computation time. Experimental results carried out on the benchmark instances show that our algorithm outperforms genetic algorithm and greedy algorithm. As compared with CPLEX solver, our algorithm can obtain all the optimal solutions on the tested instances with less computation time

Formulation and solution technique for agricultural waste collection and transport network design

Agricultural waste management in developing countries has become a challenging issue for rural planners due to the lack of an efficient planning tool. In the countries, farmers burnt agricultural waste at fields after each harvesting season to solve the issue. As a result, it has caused air and water pollution in the rural areas of the countries. In this paper, we present a mixed-integer nonlinear programming model for agricultural waste collection and transport network design that aims to stop burning waste and use the waste to produce bio-organic fertilizer. The model supports rural planners to optimally locate waste storages, and to determine the optimal set of routes for a fleet of vehicles to collect and transport the waste from the storages to the bio-organic fertilizer production facility. In the novel location-assignment-routing problem, the overall objective is to minimize total cost of locating storages, collecting waste from fields and planning vehicle routes. A solution technique is developed to linearise the mixed-integer nonlinear programming model into a model in linear form. In addition, a parallel water flow algorithm is developed to solve efficiently the large-sized instances. The efficiency of the proposed model and algorithm is validated and evaluated on the real case study in Trieu Phong district, Quang Tri province, Vietnam, as well as a set of randomly generated large-sized instances. The results show that our solution approach outperforms the general optimisation solver and tabu search algorithm. Our algorithm can find the optimal or near-optimal solutions for the large-sized instances within a reasonable time

A novel liposomal S-propargyl-cysteine: a sustained release of hydrogen sulfide reducing myocardial fibrosis via TGF-β1/Smad pathway

Purpose: S-propargyl-cysteine (SPRC; alternatively known as ZYZ-802) is a novel modulator of endogenous tissue H2S concentrations with known cardioprotective and anti-inflammatory effects. However, its rapid metabolism and excretion have limited its clinical application. To overcome these issues, we have developed some novel liposomal carriers to deliver ZYZ-802 to cells and tissues and have characterized their physicochemical, morphological and pharmacological properties. Methods :Two liposomal formulations of ZYZ-802 were prepared by thin-layer hydration and the morphological characteristics of each liposome system were assessed using a laser particle size analyzer and transmission electron microscopy. The entrapment efficiency and ZYZ-802 release profiles were determined following ultrafiltration centrifugation, dialysis tube and HPLC measurements. LC-MS/MS was used to evaluate the pharmacokinetic parameters and tissue distribution profiles of each formulation via the measurements of plasma and tissues ZYZ-802 and H2S concentrations. Using an in vivo model of heart failure (HF), the cardio-protective effects of liposomal carrier were determined by echocardiography, histopathology, western blot and the assessment of antioxidant and myocardial fibrosis markers.Results: Both liposomal formulations improved ZYZ-802 pharmacokinetics and optimized H2S concentrations in plasma and tissues. Liposomal ZYZ-802 showed enhanced cardioprotective effects in vivo. Importantly, liposomal ZYZ-802 could inhibit myocardial fibrosis via the inhibition of the TGF-β1/Smad signaling pathway. Conclusion: The liposomal formulations of ZYZ-802 have enhanced pharmacokinetic and pharmacological properties in vivo. This work is the first report to describe the development of liposomal formulations to improve the sustained release of H2S within tissues.Key word: Liposome; S-Propargyl-cysteine (SPRC, ZYZ-802); Hydrogen sulfide; Heart failure; Myocardial fibrosis; TGF-β1/Smad pathwa

ZYZ-168 alleviates cardiac fibrosis after myocardial infarction through inhibition of ERK1/2-dependent ROCK1 activation

Selective treatments for myocardial infarction (MI) induced cardiac fibrosis are lacking. In this study, we focus on the therapeutic potential of a synthetic cardio-protective agent named ZYZ-168 towards MI-induced cardiac fibrosis and try to reveal the underlying mechanism. ZYZ-168 was administered to rats with coronary artery ligation over a period of six weeks. Ecocardiography and Masson staining showed that ZYZ-168 substantially improved cardiac function and reduced interstitial fibrosis. The expression of α–smooth muscle actin (α-SMA) and Collagen I were reduced as was the activity of matrix metalloproteinase 9 (MMP-9). These were related with decreased phosphorylation of ERK1/2 and expression of Rho-associated coiled-coil containing protein kinase 1 (ROCK1). In cardiac fibroblasts stimulated with TGF-β1, phenotypic switches of cardiac fibroblasts to myofibroblasts were observed. Inhibition of ERK1/2 phosphorylation or knockdown of ROCK1 expectedly reduced TGF-β1 induced fibrotic responses. ZYZ-168 appeared to inhibit the fibrotic responses in a concentration dependent manner, in part via a decrease in ROCK 1 expression through inhibition of the phosphorylation status of ERK1/2. For inhibition of ERK1/2 phosphorylation with a specific inhibitor reduced the activation of ROCK1. Considering its anti-apoptosis activity in MI, ZYZ-168 may be a potential drug candidate for treatment of MI-induced cardiac fibrosis