In on-line integrated production–distribution problems, customers release jobs to a manufacturer that has to process the jobs and deliver them to the customers. The jobs are released on-line, that ...is, at any time there is no information about future jobs. Processed jobs are grouped into batches, which are delivered to the customers as single shipments. The total cost (to be minimized) is the sum of the total weighted flow time and the total delivery cost. Such on-line integrated production–distribution problems have been studied for the case of uncapacitated batches. We consider the capacitated case with an upper bound on the size of a batch. For several versions of the problem, we present efficient on-line algorithms, and use competitive analysis to study their worst-case performance.
•The multi-period vehicle routing problem is extended by considering service consistency goals.•We analyze the trade-off between arrival time consistency, driver consistency, and routing cost.•Our ...results support companies in finding adequate consistency goals to aim for.•A 70 percent better arrival time consistency is achieved by increasing travel time by not more than 3.84 percent, on average.•Arrival time consistency improves as a side effect of visiting each customer with a single driver.
More and more companies in the routing industry are providing consistent service to gain competitive advantage. However, improved service consistency comes at the price of higher routing cost, i.e., routing cost and service consistency are conflicting objectives. In this paper, we extend the generalized consistent vehicle routing problem (GenConVRP) by considering several objective functions: improving driver consistency and arrival time consistency, and minimizing routing cost are independent objectives of the problem. We refer to the problem as the multi-objective generalized consistent vehicle routing problem (MOGenConVRP). A multi-objective optimization approach enables a thorough trade-off analysis between the conflicting objective functions. The results of this paper should help companies in finding adequate consistency goals to aim for. Results are generated for several test instances by two exact solution approaches and one heuristic. The exact approaches are based on the ϵ-constraint framework and are used to solve small test instances to optimality. Large instances with up to 199 customers and a planning horizon of 5 days are solved by multi directional large neighborhood search (MDLNS) that combines the multi directional local search framework and the LNS for the GenConVRP. The solution quality of the heuristic is evaluated by examining five multi-objective quality indicators. We find that MDLNS is an eligible solution approach for performing a meaningful trade-off analysis.
Our analysis shows that a 70 percent better arrival time consistency is achieved by increasing travel cost by not more than 3.84 percent, on average; visiting each customer by the same driver each time is significantly more expensive than allowing at least two different drivers per customer; in many cases, arrival time consistency and driver consistency can be improved simultaneously.
The supply of water to both rural and urban centres of Nigeria is extremely poor with reference to quantity and access. The study investigated water distribution and supply in Ado-Ekiti metropolis ...applying a geospatial approach, with a view to generating baseline information to optimize water supply and distribution in the metropolis. Materials used included: a map of Ado-Ekiti with a scale of 1:50000 obtained from the Local Government Office, AdoEkiti water distribution facility map (2000) with a scale of 1:30000 obtained from the Ado-Ekiti State Water Corporation and population estimate of Ado-Ekiti from the Bureau of Statistics. Sets of structured questionnaires were used to get information from the residents and the State’s Water Corporation. The study delineated existing water distribution network of the metropolis, provided (i) a map of the service areas, (ii) information on areas with distribution problems and (iii) the per capita demand of the population as inferred from the questionnaires. A lasting solution was also proffered through the design of a water distribution network for the estimated daily water demand for the years 2019 and 2049 irrespective of the variation in water needs of the residents in the area. The Geospatial approach was found to be useful in improving the distribution system through extension of pipelines and identification of various locations for service reservoirs. Keywords: Management, reservoir, distribution problems, served, pipe-borne
The consistent vehicle routing problem (ConVRP) takes customer satisfaction into account by assigning one driver to a customer and by bounding the variation in the arrival times over a given planning ...horizon. These requirements may be too restrictive in some applications. In the generalized ConVRP (GenConVRP), each customer is visited by a limited number of drivers and the variation in the arrival times is penalized in the objective function. The vehicle departure times may be adjusted to obtain stable arrival times. Additionally, customers are associated with AM/PM time windows. In contrast to previous work on the ConVRP, we do not use the template concept to generate routing plans. Our approach is based on a flexible large neighborhood search that is applied to the entire solution. Several destroy and repair heuristics have been designed to remove customers from the routes and to reinsert them at better positions. Arrival time consistency is improved by a simple 2-opt operator that reverses parts of particular routes.
A computational study is performed on ConVRP benchmark instances and on new instances generated for the generalized problem. The proposed algorithm performs well on different variants of the ConVRP. It outperforms template-based approaches in terms of travel cost and time consistency. For the GenConVRP, we experiment with different input parameters and examine the trade-off between travel cost and customer satisfaction. Remarkable cost savings can be obtained by allowing more than one driver per customer.
This paper examines the challenge of integrated production and distribution, aiming to deliver products to customers precisely on time. Customers, situated within the transportation network, have ...predefined requirements regarding demand volume and time frames. In the first phase (F.sub.1), the problem of planning and allocation of resources is presented as FJSP, while the second phase (F.sub.2) addresses the vehicle routing problem as CVRPTW. The first phase, F.sub.1, aims to optimize manufacturing processes by appropriately scheduling production tasks to maximize productivity and minimize the time of task execution on machines. Phase 2, F.sub.2, encompasses the process of distribution to customers, seeking to minimize the number of vehicles, delivery time, and overall distance travelled. As both problems are among the most challenging in combinatorial optimization, integrating these phases into a single supply chain system poses a significant challenge in problem-solving. A mathematical formulation has been developed to include planning and task allocation in production, as well as vehicle routing, to obtain an optimal solution to the integrated problem. The input data used in the observed case study represent real data in both the first and second phases, forming one integrated supply chain system. Experimental results support the applied methodology.
This study investigates the impact of wind spatial distribution on sub-synchronous resonance (SSR), considering wind speed difference and wind turbine division. For a doubly-fed induction generator ...(DFIG) wind farm, two equivalent aggregated models, i.e. a one-DFIG model and a multi-DFIG model, are established and both simplified to impedance model for investigation. In one-DFIG model, the SSR mechanism in DFIG wind farm, and the impact of wind speed on SSR are discussed. The concept of damping is introduced to explain how DFIG SSR current changes under the negative resistance of wind farm. Then, in multi-DFIG model, DFIGs are divided into different groups based on their wind speed, and the interaction between DFIG groups is investigated. Simulations are used to validate the proposed analysis, and the results show that, multi-DFIG model performances a higher accuracy when dealing with DFIG wind spatial distribution problems compared with one-DFIG model.
In Asian Continent India is the second largest country in population. From ancient times Agriculture is the main occupation and plays a crucial role in Indian economy. Due to changes in the food ...habits, growth of technology, modernization, agriculture cropping pattern of the country in the recent years has undergone a major shift from cereal to non cereal crops cultivation especially towards Horticulture. It is refined by the human skills as a science to obtain more and more benefits. In India, one of the fastest growing sectors within the agriculture activities is Horticulture. Despite the government's efforts in offering various facilities and services to encourage farmers taking up horticultural crops, marketin g the results is difficult. The marketing of horticultural crops is a complex process. It consists of all those functions and processes involved in the movement of the product from the place of production to that of consumption. The marketing activities involve not only the functions of buying and selling but also the preparation of produce for marketing, assembling, packing, transportation, grading, storage, processing, retailing etc. The main aim of the study is to understand the farmers' perception and their Problems in selling the horticulture products.
A manufacturer has to process jobs released on-line and deliver them to customers. Preemption is allowed. Jobs are grouped into batches for delivery. The sum of the total flow time and the total ...delivery cost is minimized. Deliveries to different customers cannot be combined. We present an on-line algorithm with the competitive ratio bounded by 3+α, where α is the ratio of the largest processing time to the smallest processing time.
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