Modelling a fertiliser distribution system

Sharma, Ruchi

doi:10.1016/0377-2217(91)90142-i

Cited by 19 publications

(46 citation statements)

References 11 publications

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“…These two are strong constraints for the problem. In the formulation of pure ILP feasibility constraint (Equation (13)) is also added for solving the problem as it reduced the iterations greatly as found by Sharma [3]. The following additional cut constraint was added to pure ILP.…”

Section: Definition Of Decision Variablesmentioning

confidence: 99%

“…Geoffrion & Graves [2], Sharma [3], Sharma [4] and Kouvelis et al [5] have used weak formulation of the problem and not the strong formulations. Geoffrion & Graves [2] and Sharma [3] have attempted the Single Stage SSUWLP (Single Stage Un-Capacitated Warehouse location Problem) and they have given completely different formulations considering two different real life …”

Section: Un-capacitated/capacitatedmentioning

confidence: 99%

“…All this was possible because of the ease in Bender's approach which otherwise using branch & bound would not have been possible. Sharma [3] had also applied Bender's decomposition to a distribution problem. In this feasibility constraints were included which greatly reduced the number of Bender's iterations.…”

mentioning

confidence: 99%

“…continuous variables are not involved. Details of Benders' Decomposition method solving mixed 0 -1 integer linear program can be found in Geoffrion & Graves [2] and Sharma [3].…”

mentioning

confidence: 99%

“…Sharma [3] solved the real life fertilizer distribution system problem using Benders' Decomposition formulating it as a mixed 0 -1 integer linear program (MILP). The concept of strong and weak formulations as given by Sharma & Verma [13] also gave the hybrid formulations for the same problem.…”

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confidence: 99%

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Application of Modified Benders Decomposition to Single-Stage Multi-Commodity Multi-Period Warehouse Location Problem: An Empirical Investigation

Sharma¹,

Malviya²,

Kumar³

et al. 2016

AJOR

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In the past, researchers have applied Bender's decomposition to distribution problem and used feasibility constraint to speed up the performance of Bender's decomposition. Further, the application of Branch and Bound to single-stage multi-commodity single-period warehouse location problem (SSMCSPWLP) with strong constraints has shown that they are more effective. It was also shown in the previous research (in the context of Branch and Bound Methodology) that hybrid formulation for the single-stage single-period multi-commodity warehouse location problem yielded superior results. In this paper we apply Benders' decomposition to strong and weak formulations of single-stage multi-commodity multi-period warehouse location problem (SSMCMPWLP). As suggested in the previous literature we put feasibility constraints in the pure integer subproblem to speed up the performance of Benders' decomposition. We also develop an additional cut (constraint that is again added to pure integer sub-problem) and show that it further speeded up Benders' Decomposition. This research led to the possibility of applying Benders' Decomposition to the hybrid formulation of SSMCMPWLP in future.

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Section: Definition Of Decision Variablesmentioning

confidence: 99%

Section: Un-capacitated/capacitatedmentioning

confidence: 99%

mentioning

confidence: 99%

“…continuous variables are not involved. Details of Benders' Decomposition method solving mixed 0 -1 integer linear program can be found in Geoffrion & Graves [2] and Sharma [3].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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