Harvesting Problem Research Articles

Consumption of liquefied petroleum gas and its determinants: A prospect for indiscriminate tree harvesting in Imo State, Nigeria

The study analysed the consumption of liquefied petroleum gas and its determinants as a prospect for indiscriminate tree harvesting in Imo State, Nigeria. A total number of 96 questionnaires were distributed but only 90 of them were returned. Data collected were analysed using both descriptive and inferential statistics. Result shows that the weekly fuel wood and liquefied petroleum gas consumed by the households in the study area were 514.326MJ (37.27KG) and 65.92MJ (1.43KG) respectively. The result also identified indoor pollution, eye defect and loss of biodiversity with weighted means of 2.64, 3.00 and 2.67 respectively as very serious problems of fuel wood use. Result showed that clean fuels (as well as afforestation), ethanol cook stove, crop residue/animal dung and solar/water energy sources which ranked 1st, 2nd, 3rd and 4th respectively were the major prospects for indiscriminate tree harvesting in the study area. Results also indicated that at 1% levels of significance, price of liquefied petroleum gas, price of kerosene, household expenditure, household size and number of times electricity was available per month were the majordeterminants of liquefied petroleum gas consumption in the study areas. Given the urgency of the clean energy access, the paper recommends that relevant stakeholders should prioritize efforts and financial supports geared toward the alleviation of the problems of indiscriminate tree harvesting. It also advocates for LPG subsidization to encourage more users of the fuel.
 Keywords: Indiscriminate wood harvesting, loss of bio-diversity, clean energy

Optimizing tactical harvest planning for multiple fruit orchards using a metaheuristic modeling approach

In a fruit harvest season, the fruit must be collected during a relatively short period of intense activity. Moreover, large fruit export companies commonly manage multiple orchards where the resources and labor are shared, making the decision process more complex. In this study, we address this harvest problem by proposing a mixed integer linear programming model for supporting tactical decisions during the harvest season in order to reduce total costs. This includes costs related to the fruit not reaching maturity and the number of harvest days. Due to the difficulty of solving this model optimally when real cases are considered, we developed a GRASP metaheuristic method. We compared the GRASP metaheuristic solution to the best integer solution obtained by an exact method using a real case. We observed that the metaheuristic produced a solution in less computational time than the best integer solution. The total costs obtained by the GRASP metaheuristic were two percent greater than the total cost obtained by the best integer solution. Additionally, we analyzed two scenarios to establish if the joint resource planning of the orchards would allow a cost reduction. The GRASP metaheuristic provides orchard managers with a harvest plan in a timely manner and adds greater flexibility to the decision process. The proposed model can be used to plan the harvesting of a variety of fresh fruits.

A symplectic pseudospectral method for constrained time-delayed optimal control problems and its application to biological control problems

ABSTRACT Time-delays are often involved in modelling biological processes, which arise more difficulties for the control task. In fact, once the control goal is given, a constrained optimal control problem can be formulated to describe the biological control mission. However, it’s almost impossible to obtain analytical solutions for such complicated problems, especially for those with high nonlinearity and complex constraints. In this paper, a symplectic pseudospectral method for solving nonlinear optimal control problems of constrained stated-delayed system is developed. The original nonlinear problem is transformed into a series of linear-quadratic optimal control problems by the successive convexification technique at the first implementation. By applying the local Legendre-Gauss-Lobatto pseudospectral method and the parametric variational principle, each of the transformed linear-quadratic problems is converted into a standard linear complementarity problem which can be solved easily by the Lemke’s method. The cost functional, system dynamics and constraints can be generally nonlinear functions of state, control and time variables. and three kinds of inequality constraints, i.e. pure-state, pure-control and mixed state-control, can be treated under a uniform framework. The developed symplectic pseudospectral method is finally validated by an optimal harvesting problem and an optimal vaccination problem.

Harvesting and seeding of stochastic populations: analysis and numerical approximation

We study an ecosystem of interacting species that are influenced by random environmental fluctuations. At any point in time, we can either harvest or seed (repopulate) species. Harvesting brings an economic gain while seeding incurs a cost. The problem is to find the optimal harvesting-seeding strategy that maximizes the expected total income from harvesting minus the cost one has to pay for the seeding of various species. In Hening et al. (J Math Biol 79(2):533-570, 2019b) we considered this problem when one has absolute control of the population (infinite harvesting and seeding rates are possible). In many cases, these approximations do not make biological sense and one must consider what happens when one, or both, of the seeding and harvesting rates are bounded. The focus of this paper is the analysis of these three novel settings: bounded seeding and infinite harvesting, bounded seeding and bounded harvesting, and infinite seeding and bounded harvesting. Even one dimensional harvesting problems can be hard to tackle. Once one looks at an ecosystem with more than one species analytical results usually become intractable. In order to gain information regarding the qualitative behavior of the system we develop rigorous numerical approximation methods. This is done by approximating the continuous time dynamics by Markov chains and then showing that the approximations converge to the correct optimal strategy as the mesh size goes to zero. By implementing these numerical approximations, we are able to gain qualitative information about how to best harvest and seed species in specific key examples. We are able to show through numerical experiments that in the single species setting the optimal seeding-harvesting strategy is always of threshold type. This means there are thresholds [Formula: see text] such that: (1) if the population size is 'low', so that it lies in [Formula: see text], there is seeding using the maximal seeding rate; (2) if the population size 'moderate', so that it lies in [Formula: see text], there is no harvesting or seeding; (3) if the population size is 'high', so that it lies in the interval [Formula: see text], there is harvesting using the maximal harvesting rate. Once we have a system with at least two species, numerical experiments show that constant threshold strategies are not optimal anymore. Suppose there are two competing species and we are only allowed to harvest or seed species 1. The optimal strategy of seeding and harvesting will involve lower and upper thresholds [Formula: see text] which depend on the density [Formula: see text] of species 2.

Model-checking precision agriculture logistics: the case of the differential harvest

The development, in the last decades, of technologies for precision agriculture allows the acquisition of crop data with a high spatial resolution. This offers possibilities for innovative control and raises new logistics issues that may be solved using discrete event models. In vineyards, some technologies make it possible to define zones with different qualities of grapes and sort the grapes at harvest to make different vintages. In this context, the Differential Harvest Problem (DHP) consists in finding a trajectory of the harvesting machine in the field in order to obtain at least a given quantity of higher quality grapes and minimising working time. In available literature, the DHP has been solved using Constraint Programming. In this paper, we investigate if it is possible to solve the DHP using the Cost Optimal Reachability Analysis feature of a model-checking tool such as UPPAAL-CORA. A model named DHP_PTA has been designed based on the priced timed automata formalism and the UPPAAL-CORA tool. The method made it possible to obtain the optimal trajectory of a harvesting machine for a vine plot composed of up to 14 rows. The study is based on real vineyard data. This paper is an extended version of a communication presented at WODES 2018 (Saddem-Yagoubi IFAC-PapersOnLine 51(7):57–63, 2018).

A joint optimization framework for wheat harvesting and transportation considering fragmental farmlands

Crop harvesting and transportation should be considered as an integrated system to be optimized aiming to reduce the total operational costs. However, current studies mainly focused on how to reduce operational cost for a link, not from integrated perspective. In this paper, a joint problem which consists of harvesting and transportation problem is implemented and optimized to meet the better schedule with less operational costs. The harvesting and transportation problems could respectively be considered as a vehicle routing problem with multiple trips and a transportation problem,. These two problems should be optimized jointly because combine-harvesters and transporters should be synchronized at fragmental farmlands. A mixed integer programming is employed considering all constraints arising in the joint optimized framework. Furthermore, a hybrid algorithm is presented to find an optimum solution for this problem. Five different cases are used to verify the performance of the hybrid algorithm. Besides, our real cases are used to prove that there is a significant improvement if the integrated wheat harvesting and transportation policy is adopted. The results indicate that the model and algorithm is an effective approach to help farmers to decrease reaping costs.

Cooperative Small Cell HetNets With Dynamic Sleeping and Energy Harvesting

This paper considers a heterogenous wireless cellular network (HetNet) where many small base stations (SBS) coexist. SBSs can be deactivated and put to sleep to save energy and are equipped with two power sources, harvested energy (HE) and a grid power source, where an SBS will use its available HE to serve the associated users first. Then, the SBS will request any shortage of its energy from other active or deactivated SBSs that have a surplus of HE. Finally, if there is still an energy shortage, the SBS will use power drawn from the grid. This transfer of energy is facilitated through the use of the promising smart grid (SG)technology. We investigate the grid energy minimization problem by optimizing both the transmission power and activation/deactivation (dynamic sleeping) of the SBSs. However, since the formulated problem is a mixed integer nonLinear problem (MINLP), generalized Benders decomposition (GBD) is used to decompose the problem into two subproblems: user association and energy harvesting which are solved iteratively. Further, a new heuristic approach is proposed that provides a computationally efficient algorithm to solve and optimize the user association and energy harvesting problems of the system model. This approach uses network centrality to develop a measuring parameter, base station centrality (BSC), of SBS centrality in the network. BSC is presented to mark the SBSs that have the most potential to be deactivated without affecting the quality of service (QoS) of users. Finally, extensive simulations are performed to verify the superiority of the proposed BSC-based strategy over GBD in terms of operational cost.

Thin‐Layered Photocatalysts

AbstractSemiconductor photocatalysis, a green and sustainable technology, is of great significance for solving environmental pollution and energy shortages. However, the common problems of inefficient light harvesting, rapid recombination of electron–hole pairs, and low surface reactive reaction sites for photocatalysts urgently need to be solved. In this regard, thin‐layered photocatalysts are considered to be one of the most promising candidates for addressing these issues, due to their unique surface and electronic properties. In this review, the various strategies for constructing thin‐layered photocatalysts are summarized, and emphasis is given to approaches for optimizing the photocatalytic performance of the thin‐layered materials, which can be classified into surface engineering and junction construction. In addition, the photocatalytic applications of thin‐layered materials, i.e., water splitting, CO2 reduction, nitrogen fixation, and molecule oxygen activation, are summarized. Finally, based on current achievements in thin‐layered photocatalysts, their future development and challenges are discussed.

Analysis of optimal harvesting of a predator-prey model with Holling type IV functional response

This paper investigates a series of harvesting problems of a harvested predator-prey system with Holling type IV functional response. The bionomic equilibrium, the maximum sustainable total yield (MSTY) and the optimal economic profit of the proposed system are studied. It is proved that the MSTY does not exist under the independent harvesting mode, while it may be found with the same predator and prey harvesting efforts mode. By applying the Bang-Bang control and the singular control to the harvesting strategy, the optimal equilibrium state of the discussed system converges faster than that of the system utilizing a single harvesting strategy with the fixed harvesting effort. The MISER 3 software package is adopted to obtain the optimization schemes of two control problems by using the control parameterization method. The findings of our study provide a theoretical basis for biological resource management.

Analyticity of free boundary in an optimal harvesting problem

This note revisits an optimisation problem pertaining to the optimal harvesting of a marine species. The existence of solutions and the corresponding optimal conditions they satisfy have already been proved. It is known that the optimal solutions can be identified with n-dimensional shapes. We will obtain an interesting result concerning the free boundary of the optimal shapes. Indeed, we will prove that if a parameter in the admissible set is kept sufficiently small then the free boundaries will be real analytic hypersurfaces.

Exploiting double jumping phenomenon for broadening bandwidth of an energy harvesting device

The steady state response of a particular harvesting system is investigated under the condition of external and internal resonance, with emphasis on the double jump phenomenon. Following the trend of recent researches on exploring nonlinearity aspects for broadening the frequency resonance bandwidth, the problem of effective energy harvesting from a broadband source is dealt with. The proposed harvester can be embedded within vibrational structures and can dually act as a vibration absorber. The governing non-linear partial differential equations are truncated into a set of perturbed equations via Galerkin method. The method of multiple scales is applied to derive the modulated amplitude versus frequency at the vicinity of flapwise and chordwise primary resonances, as well as around other internal resonance frequencies. The amplitude-frequency response plot reveals resonance peaks bending to the left and right, i.e., splitting into two different tongues in contrast to conventional jumps which lean only toward higher or lower frequency directions. Numerical results demonstrate that this internal resonance-based harvesting design can produce sufficient power for the consumption of typical MEMS devices.

Nutrients removal from piggery wastewater coupled to lipid production by a newly isolated self-flocculating microalga Desmodesmus sp. PW1

A newly isolated microalgal strain, Desmodesmus sp. PW1, possessing not only high potential for removing nitrogen and phosphorous from piggery wastewater but excellent self-flocculating ability, was provided here. Strain PW1 grew well in diluted and undiluted piggery wastewater, and could effectively remove total nitrogen and total phosphorus with removal rates up to 90% and 70%, respectively. In the laboratory scale by 30-L photobioreactor, microalga also performed well in TN (65.3%) and TP (83.5%) removal. Strain PW1 cultivated in the stationary phase achieved high self-flocculating efficiency (>90%) in 2.5 h of settling; meanwhile, temperature and pH slightly influenced on the flocculation. The potential mechanism on self-flocculation was considered related to hydrophobic extracellular polymeric substances. Furthermore, the fatty acid compositions of PW1 were mainly hexadecanoic acid, oleic acid and linoleic acid. Taken together, Desmodesmus sp. PW1 was the promising candidate to overcome the microalgae harvesting problem in piggery wastewater treatment.

On the problem of nightshade vegetables harvesting in conditions of limited land use and protected ground

The paper is devoted to the analytical justification of nightshade vegetables harvesting in conditions of limited land use and protected ground, both by direct and reusable methods. The article has an analytical research character, which is expressed in the fact that the analysis of the method of nightshade vegetables harvesting is given. The main trend of technology development and improvement of its design to advance the quality parameters of harvesting is identified. As a result of the work done, the conclusion is made about the importance of nightshade vegetables harvesting and in the development of new varieties in the context of modern approaches to the cultivation of nightshade vegetables.

Solving forest harvesting problem with artificial intelligence approaches: An example in Taiwan

In this paper, we study the forest harvesting problem (FHP). A forest is assumed to be divided into several identical square units, and each unit has its harvesting value based on its type. Harvesting a unit will affect the growth and values of its neighboring units. In this FHP, the best harvesting plan of a unit must be identified to maximize three various objectives simultaneously. The FHP is a multiobjective mathematical and an NP-hard problem. We apply three artificial intelligence algorithms, namely, immune algorithm, genetic algorithm, and particle swarm optimization, for maximizing the weighted objective to solve the FHP. We also solve the following two sets of test problems: (i) a set of randomly generated FHP problems and (ii) a practical problem in Taiwan. Numerical results show the performance of the three algorithms for the test problems. Finally, we compare and discuss the effects of various weights for the three objectives.

Global analysis and optimal harvesting for a hybrid stochastic phytoplankton-zooplankton-fish model with distributed delays.

In this paper, we formulate a phytoplankton-zooplankton-fish model with distributed delays and hybrid stochastic noises involving Brownian motion and Markov chain, and propose an optimal harvesting problem pursuing the maximum of total economic income. By global analysis in terms of some system parameters, we investigate the dynamical behaviors on the well-posedness, bounded- ness, persistence, extinction, stability and attractiveness of the solutions for the stochastic delayed system. Moreover, we provide sufficient and necessary condition ensuring the existence of the optimization solution for the optimization problem and obtain the optimal harvesting effect and the maximum of sustainable yield. Lastly, two numerical examples and their simulations are given to illustrate the effectiveness of our results.

Immobilization of Microalgae.

Several microalgae synthesize metabolites of great commercial interest. Microalgae also act as filters for wastewater N and P, heavy metals, and xenobiotic compounds. However, the cost-effective harvesting of microalgae is one of the major bottlenecks limiting the microalgal biomass applications. In this context, immobilization of algal cells has been proposed for circumventing the harvest problem as well as retaining the high-value algal biomass for further processing. In recent years, innovative approaches have been employed in the field of coimmobilization and microencapsulation, which have proved the superiority of immobilized cells over the free cells. Further, the development in the field of biosensor technology with immobilized microalgae presents an early warning device to monitor pollutants in natural waters. This chapter reviews the various applications of immobilized microalgae and addresses the specific methods concerning the production of coimmobilized beads and the protocol for construction of optical algal biosensors.

Design on the Winter Jujubes Harvesting and Sorting Device

According to the existing problems of winter jujube harvesting, such as the intensive labor of manual picking, damage to the surface of winter jujubes, a winter jujube harvesting and sorting device was developed. This device consisted of vibration mechanism, collection mechanism, and sorting mechanism. The eccentric vibration mechanism made the winter jujubes fall, and the umbrella collecting mechanism can collect winter jujube and avoid the impact of winter jujube on the ground, and the sorting mechanism removed jujube leaves and divided the jujube into two types, and the automatic leveling mechanism made the device run smoothly in the field. Through finite element analysis and BP (Back Propagation) neural network analysis, the results show that: The vibration displacement of jujube tree is related to the trunk diameter and vibration position; the impact force of winter jujubes falling is related to the elastic modulus of umbrella material; the collecting area can be increased four times for each additional step of the collection mechanism; jujube leaves can be effectively removed when blower wind speed reaches 45.64 m/s. According to the evaluation standard grades of the jujubes harvesting and sorting, the device has good effects and the excellent rate up to 90%, which has good practicability and economy.

Optimal Harvesting for Size-Dependent Control

We investigate some optimal harvesting problems concerning the age-structured population dynamics. The goal is to maximize the profit with respect to a size-dependent harvesting effort. The harvesting is made either by fishing or by hunting. For each studied problem, we state the necessary optimality conditions and use them to get the structure of the optimal control. For the problem related to hunting, we derive an iterative algorithm to improve at each step the harvesting effort, in order to increase the profit. Numerical tests are performed to show that the proposed methods are effective.

Kinetic Energy Harvesting for Wearable Medical Sensors.

The process of collecting low-level kinetic energy, which is present in all moving systems, by using energy harvesting principles, is of particular interest in wearable technology, especially in ultra-low power devices for medical applications. In fact, the replacement of batteries with innovative piezoelectric energy harvesting devices can result in mass and size reduction, favoring the miniaturization of wearable devices, as well as drastically increasing their autonomy. The aim of this work is to assess the power requirements of wearable sensors for medical applications, and address the intrinsic problem of piezoelectric kinetic energy harvesting devices that can be used to power them; namely, the narrow area of optimal operation around the eigenfrequencies of a specific device. This is achieved by using complex numerical models comprising modal, harmonic and transient analyses. In order to overcome the random nature of excitations generated by human motion, novel excitation modalities are investigated with the goal of increasing the specific power outputs. A solution embracing an optimized harvester geometry and relying on an excitation mechanism suitable for wearable medical sensors is hence proposed. The electrical circuitry required for efficient energy management is considered as well.

Using hybrid algorithm to reduce non-working distance in intra- and inter-field logistics simultaneously for heterogeneous harvesters

Reducing the non-working distance for agricultural vehicles is beneficial for reducing the total operational costs for farmers. In this study, we optimize the non-working distance in intra- and inter-fields simultaneously for harvesters while harvesting rice. A mixed integer programming is presented for optimizing the rice harvesting problem, where a similar working time for all harvesters are considered based on a real case. Besides, in this model, two kinds of fields, namely moist and non-moist fields are considered, where the first can only be harvested by crawler harvesters while the second can be harvested by any type of harvester. This model aims to find an optimal schedule for the harvesters. A hybrid algorithm using both adaptive large neighborhood search and tabu search techniques is implemented to optimize the problem. A case study is considered to verify the performance of the hybrid algorithm. The results indicate that the hybrid algorithm is an effective method for solving the rice harvesting problem because the total non-working distance could be improved significantly by 15.3%. The proportion of moist fields is analyzed because it influences the schedule significantly. When compared to the traditional method for optimizing the non-working distance for harvesters, the total non-working distance in this method could be reduced by 6.2%. This paper provides farmers with a general framework for reducing the non-working distance in intra- and inter-field logistics, which results in a more efficient performance of the harvesters in the fields.