Sugar beet transportation problem under growers’ equity regulations: Metaheuristic approach

A greedy randomized adaptive search procedure (GRASP) for minimum 2-fold connected dominating set problem

The weighted maximal planar graph (WMPG) is practically important in the laying out of facilities in modern manufacturing environments. Given a weighted complete graph, the WMPG seeks to find a sub-graph such that it is planar—it can be embedded on the plane without any arcs intersecting, and it is maximal—no additional arc can be added to the sub-graph without destroying its planarity, and it also has the maximal sum of arc weights. In this paper, an integer linear programming (ILP) model is newly introduced for the problem. Two meta-heuristics are then derived from the ILP relaxation. The first meta-heuristic considers all variables with fractional values greater than half in the ILP relaxation to build an initial sub-graph from which a planar sub-graph is extracted using greedy random adaptive search procedure (GRASP) and augmented by triangulation of faces. The second meta-heuristic considers only arcs with integer values in the ILP relaxation. The remaining arcs are then sorted in descending order of their weights, for selection and insertion with a planarity testing procedure, to obtain a feasible solution using GRASP. Computational results are reported on a set of 100 test instances of size varying from 20 to 100 facilities. The computational results demonstrate the tightness of the new upper bound when compared to the classical one as well as the good performance of the proposed metaheuristics when compared to the best-known procedures in the literature in terms of solution quality and computational requirement. Finally, the paper presents a successful integration of GRASP with classical optimisation approaches and should be attempted for other optimisation problems.

This paper considers a production–distribution problem that consists of defining the flow of produced products from manufacturing plants to clients (markets) via a set of warehouses. The problem also consists of defining the location of such warehouses that have unlimited storage capacity. This problem is known in the literature as the three-echelon uncapacitated facility location problem (TUFLP), and is known to be NP-hard when the objective function is to minimize the total cost of warehouse location and production and distribution of products. This paper proposes a Greedy Randomized Adaptive Search Procedure (GRASP) to solve the multi-item version of the TUFLP. Computational experiments are conducted using known instances from the literature. Solutions obtained using GRASP are compared against both optimal solutions and lower bounds obtained using mathematical programming. Results show that proposed algorithm performs well, obtaining good solutions (and even the optimal values) in less computational time than the mixed-integer linear programming model.

The article analyzes the current situation in the world sugar market, in particular, an analysis of sugar production and consumption, sugar exports and imports, the price situation on world exchanges, both for beet sugar and for cane sugar. It is noted that Ukraine's influence on the world sugar market is not significant, since its share in global production barely exceeds 1%. It is established that the largest sugar producers in the world are Brazil, India, the EU, China and Thailand, whose share in global production reaches 60% every year. In some years, the top five may include other countries, in particular the USA and Pakistan, it is the first five that are decisive from the point of view of the world market. The author notes that the main world producers of cane sugar are Brazil and India, and the largest producers of both sugar beets and, accordingly, beet sugar are the countries of the European Union. China and the USA combine the cultivation of sugar beets and sugar cane and, accordingly, the production of sugar from them. It is argued that the preservation of sugar beet cultivation, despite cheaper cane, is a reflection of global trends in the confrontation between beet and cane sugar production and indicates the strategic importance of sugar beets in maintaining the balance of agricultural production. Among the main exporting countries, Brazil is highlighted, which has been the world leader in sugar exports for several decades in a row and traditionally exports 60-75% of sugar produced. Fluctuations in this indicator depend on the volume of domestic production and the situation on the world market. It is noted that on the world market over the past five years, world prices for white sugar and raw sugar have almost doubled. An increase in world prices for sugar is predicted, which is due to a decrease in the production of raw sugar and sugar in Brazil due to a prolonged drought and an increase in the use of sugar cane for ethanol production in this country. It was concluded that for the further development of the domestic sugar market it is necessary to intensify trade in sweet products, to search for its niche in the world sugar market, having the need for this and potential opportunities. At the state level, it is necessary to determine the place of Ukraine in world sugar production, export opportunities, competitiveness of domestic sugar products in the world market, in order to develop an export-import policy for this strategically important product for the country in the future. Key words: world sugar market, production, consumption, export, import, prices.

Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem

Solving Integer Linear Programming (ILP) models generally lies in the category of NP-hard problems. Therefore, as the size of ILP models grows, the efficiency of exact algorithms for solving the models reduced significantly and for large models it is not possible to have the result. Genetic Algorithm (GA) is a metaheuristic method capable of adjusting and redesigning parameters and operations according to the characteristics of ILP models. Still GA has huge search space for large models and parallelization is a suitable technique to tackle this problem. This paper presents a scalable parallel GA to solve large ILP models derived from behavioral synthesis of digital circuits. We show that although models have non-binary variables, only binary variables are sufficient for coding chromosomes. We also use ”unknown” values for some genes to decrease the likelihood of inconsistency in the encoded constraints. Our experiments verify the efficiency and scalability of the proposed algorithm on multicore platforms. The proposed method outperforms IBM ILOG CPLEX 12.6 and MI-LXPM algorithm where the ILP models include 550 to 2258 int / binary decision variables. Also, the results indicate that the saturation point of using parallel processing elements for solving the large ILP models is at least 60.

Reducing expensive raw material waste is an important goal in the industry. In this paper, two-dimensional irregular cutting stock problem—a nesting problem that differs from other in their irregular shape of the pieces—with demand is studied, in which the required pieces has to be produced from large rectangular sheet minimizing material waste. Structure of this problem made it intractable for practical applications such that exact algorithms are not able to solve it in a reasonable time. Greedy randomized adaptive search procedure (GRASP) meta-heuristic algorithm is adapted to tackle the problem by providing high-quality solution in an appropriate time. The algorithm does not depend on the shape (convexity and regularity) of pieces and is able to deliver an optimum solution for instances up to 30 pieces of 7 different types. In addition, computational results are provided for different test problems from the related literature.

This paper delves into the multi-port berth allocation problem (MBAP), enriching the traditional berth allocation problem (BAP) with vessel speed optimization (VSO). In the MBAP, it is assumed that there is cooperation between the port and the shipping companies, and the operation of the vessels and the ports is planned to maximize the overall benefits. Exploring this potential collaboration between ports and shipping entities has the potential to mitigate, or even resolve, the challenges plaguing maritime transportation, e.g., port congestion and suboptimal vessel schedules, to ultimately enhance the efficiency of maritime trade. In this paper, a new mixed-integer linear programming (MILP) model for the MBAP is formulated, which attempts to minimize the total cost incurred during operations, with various constraints such as vessel sailing, the vessel space–time relationship in ports, and the planning period. Meanwhile, an innovative variable neighborhood search (VNS) algorithm is presented, in which the initial solution generation method and neighborhood structures are proposed according to the MBAP characteristics. Furthermore, two sets of MBAP instances are generated to test the proposed MILP and VNS, of which the first set is based on real-world port data and the second on existing studies. The numerical experiments verify that the VNS can efficiently and reliably solve instances of all scales, with each neighborhood structure contributing uniquely to the iterative process. In addition, by analyzing the impact of varying oil prices on the MBAP, the study offers valuable management insights. Finally, a case study based on real data from a port group in the Yangtze River Basin is presented to further demonstrate the necessity of considering vessel service time window and planning period in the MBAP as well as the important role of the VSO in scheduling.

As one of the most popular supply chain management problems, the Vehicle Routing Problem (VRP) has been thoroughly studied in the last decades, most of these studies focus on deterministic problem where the customer demands are known in advance. But the Vehicle Routing Problem with Stochastic Demands (VRPSD) has not received enough consideration. In the VRPSD, the vehicle does not know the customer demands until the vehicle arrive to them. This paper use a hybrid algorithm for solving VRPSD, the hybrid algorithm based on Particle Swarm Optimization (PSO) Algorithm, combines a Greedy Randomized Adaptive Search Procedure (GRASP) algorithm, and Variable Neighborhood Search (VNS) algorithm. A real number encoding method is designed to build a suitable mapping between solutions of problem and particles in PSO. A number of computational studies, along with comparisons with other existing algorithms, showed that the proposed hybrid algorithm is a feasible and effective approach for Vehicle Routing Problem with Stochastic Demands.

Strategic observation of power grids for reliable monitoring

Tour recommendation is popular nowadays for providing the best-fit route plans to tourists. Existing applications only focus on the sequences design of Points of Interest (POIs) while ignore the detailed information in large-scale POIs. To further satisfy tourists’ demands, we propose Embedded Tour (eTOUR), a two-layer framework that takes these large-scale POIs, which we call Super-POIs, into account. The framework is first divided into Outer Model and Inner Model and then combined by an Embedded GRASP-VNS Algorithm based on an embedding strategy. For Outer Model, we apply Greedy Randomized Adaptive Search Procedure (GRASP) for route construction and Variable Neighborhood Search (VNS) for local search. During the outer route construction process, Super-POI is first treated as a “meta node” and in the late period, inner route is revised dynamically to adapt to the outer route where DFS-based Tree Search with Pruning is applied. Furthermore, we consider a special case in the Super-POI and modify the solution of Chinese Postman Problem to reduce the complexity. Finally, experiments based on real datasets demonstrate the effectiveness of our proposal.

p-Median based formulations with backbone facility locations

An Optimal Cross-Layer Scheduling for Periodic WSN Applications

The work summarizes changes, which involved the sugar and sugar beet production in Turkey and in Poland, in the years 1995-2014. Sugar beet area in Turkey has decreased by 7% and in Poland by 48%. Harvest has increased by 51% in Turkey and has remained unchanged in Poland. Sugar beet yield has increased: in Turkey by 63% and in Poland by 97%. 71% farmers have stopped cropping sugar beet, while in Poland this share has been 87%. Mean plantation size has increased in Turkey by over a factor of 2 (compared to 1997), while in Poland it has been by a factor of almost 4. Sugar production in Turkey has dropped by 13% (compared to 1997) and in Poland it has grown by 29%. Three new sugar plants started operation in Turkey in the years 1995-2014. In Poland 58 facilities shut down. Turkey’s securing position of major sugar producer is to be expected, under the conditions of increased pace of production concentration and implementing new production technologies. Withdrawal of sugar production quotas in the EU resulted in increased sugar beet spring sowing in several member states, including Poland. Further developments in 2018 and in the following years shall depend on the profitability of sugar beet crops and of sugar production. Significant influence is also to be expected from the isoglucose competition, production of which is to enjoy quotas withdrawal, as well.

This paper focus on the routing, modulation level and spectrum allocation (RMLSA) problem in the next generation datacentre networks, which own the advantages of both Elastic Optical Networks (EON) and Software Defined Networking (SDN). We proposes an Integer Linear Programming (ILP) model for this problem. Simulation results show the ILP model achieves an outstanding load balancing performance.