Matches in SemOpenAlex for { <https://semopenalex.org/work/W1849520090> ?p ?o ?g. }
Showing items 1 to 77 of
77
with 100 items per page.
- W1849520090 endingPage "91" @default.
- W1849520090 startingPage "78" @default.
- W1849520090 abstract "Product distribution problem is modeled as a bi-level programming.Optimal assignment for problems in which supplies cannot be split is given.5 algorithms are proposed for solving lower-level problem in the bi-level model.Effectiveness's of all algorithms are compared with the solution from CPLEX.Waste system of Northern Thailand is studied and compared with existing work. The design of distribution network influences the performance of supply chain systems. A well-designed distribution network can help a supply chain system to achieve maximum profits or minimize total cost. In this work, algorithms are designed to allocate customer demands to the distribution centers (DCs) in the supply chain network. The best locations for DCs and production distributions through DC in this work are found via a bi-level programming model. The upper-level model under the firm's consideration is to determine the optimal locations for DCs and allocate supplies to minimize the total cost, while the lower-level model is to minimize the total transportation cost of all customers. In this work, the demands of customer (or the demands of DC) can be split among DCs (or plants). Propositions for optimal assignment are presented where supplies cannot be split. All 5 algorithms are proposed to solve each level of the problem. The priorities in allocating process in each algorithm are different, taking into account the structure of the problem. The effectiveness of these algorithms are compared with the optimal/best solutions found using CPLEX and an existing algorithm. The simulation results show that all of the proposed algorithms are superior to CPLEX in large-scale problems. The proposed algorithms can execute up to 4200 DCs and 4200 customers while CPLEX can execute only problems up to 500?×?500 in size. Experiments are done to solve the municipal waste system (3,211 demand nodes and up to 48 DCs) covering 5 provinces of Northern Thailand." @default.
- W1849520090 created "2016-06-24" @default.
- W1849520090 creator A5007526829 @default.
- W1849520090 creator A5028094788 @default.
- W1849520090 date "2016-02-01" @default.
- W1849520090 modified "2023-10-02" @default.
- W1849520090 title "Product distribution via a bi-level programming approach: Algorithms and a case study in municipal waste system" @default.
- W1849520090 cites W1972079012 @default.
- W1849520090 cites W1985270863 @default.
- W1849520090 cites W1986517752 @default.
- W1849520090 cites W1991984686 @default.
- W1849520090 cites W2000618761 @default.
- W1849520090 cites W2004492465 @default.
- W1849520090 cites W2014252819 @default.
- W1849520090 cites W2023858465 @default.
- W1849520090 cites W2031264011 @default.
- W1849520090 cites W2041085006 @default.
- W1849520090 cites W2042943043 @default.
- W1849520090 cites W2047217382 @default.
- W1849520090 cites W2048584862 @default.
- W1849520090 cites W2051615652 @default.
- W1849520090 cites W2061228544 @default.
- W1849520090 cites W2065608738 @default.
- W1849520090 cites W2086076641 @default.
- W1849520090 cites W2088825679 @default.
- W1849520090 cites W2106601208 @default.
- W1849520090 cites W2122079623 @default.
- W1849520090 cites W2140145913 @default.
- W1849520090 cites W2163089608 @default.
- W1849520090 cites W2169289966 @default.
- W1849520090 cites W2259507927 @default.
- W1849520090 cites W4250535541 @default.
- W1849520090 doi "https://doi.org/10.1016/j.eswa.2015.08.053" @default.
- W1849520090 hasPublicationYear "2016" @default.
- W1849520090 type Work @default.
- W1849520090 sameAs 1849520090 @default.
- W1849520090 citedByCount "26" @default.
- W1849520090 countsByYear W18495200902017 @default.
- W1849520090 countsByYear W18495200902018 @default.
- W1849520090 countsByYear W18495200902019 @default.
- W1849520090 countsByYear W18495200902020 @default.
- W1849520090 countsByYear W18495200902021 @default.
- W1849520090 countsByYear W18495200902022 @default.
- W1849520090 countsByYear W18495200902023 @default.
- W1849520090 crossrefType "journal-article" @default.
- W1849520090 hasAuthorship W1849520090A5007526829 @default.
- W1849520090 hasAuthorship W1849520090A5028094788 @default.
- W1849520090 hasConcept C11413529 @default.
- W1849520090 hasConcept C2524010 @default.
- W1849520090 hasConcept C33923547 @default.
- W1849520090 hasConcept C41008148 @default.
- W1849520090 hasConcept C90673727 @default.
- W1849520090 hasConceptScore W1849520090C11413529 @default.
- W1849520090 hasConceptScore W1849520090C2524010 @default.
- W1849520090 hasConceptScore W1849520090C33923547 @default.
- W1849520090 hasConceptScore W1849520090C41008148 @default.
- W1849520090 hasConceptScore W1849520090C90673727 @default.
- W1849520090 hasLocation W18495200901 @default.
- W1849520090 hasOpenAccess W1849520090 @default.
- W1849520090 hasPrimaryLocation W18495200901 @default.
- W1849520090 hasRelatedWork W2003465964 @default.
- W1849520090 hasRelatedWork W2333698505 @default.
- W1849520090 hasRelatedWork W2351491280 @default.
- W1849520090 hasRelatedWork W2358668433 @default.
- W1849520090 hasRelatedWork W2371447506 @default.
- W1849520090 hasRelatedWork W2386767533 @default.
- W1849520090 hasRelatedWork W2390279801 @default.
- W1849520090 hasRelatedWork W2748952813 @default.
- W1849520090 hasRelatedWork W2899084033 @default.
- W1849520090 hasRelatedWork W303980170 @default.
- W1849520090 hasVolume "44" @default.
- W1849520090 isParatext "false" @default.
- W1849520090 isRetracted "false" @default.
- W1849520090 magId "1849520090" @default.
- W1849520090 workType "article" @default.