Solution of Multi-Objective Transportation Problem Via Fuzzy Programming Algorithm
Osuji,
George A.,
Okoli Cecilia N.,
Opara,
Jude
Issue:
Volume 2, Issue 4, August 2014
Pages:
71-77
Received:
9 July 2014
Accepted:
15 July 2014
Published:
30 July 2014
Abstract: This paper is on the solution of multi-objective transportation problem via fuzzy programming algorithm. The data for this paper was collected by an egg dealer in whose main office is located at Orji Owerri Imo State Nigeria, who supplies the product to different wholesalers (destinations) after taking it from different poultry farm (sources), and the time and cost of transportation from source i to destination j were recorded. TORA statistical software was employed in the data analysis, and the results of the analysis revealed that if we use the hyperbolic membership function, then the crisp model becomes linear. The result also revealed that the optimal compromise solution does not alter if we compare it with the solution obtained by the linear membership function. Thus, if we compare it with the solution obtained by the linear membership function, it is shown that the fuzzy optimal values do not depend on the chosen membership function be it linear or non-linear membership function.
Abstract: This paper is on the solution of multi-objective transportation problem via fuzzy programming algorithm. The data for this paper was collected by an egg dealer in whose main office is located at Orji Owerri Imo State Nigeria, who supplies the product to different wholesalers (destinations) after taking it from different poultry farm (sources), and ...
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Dynamic Pricing Research on Perishable Products under Consumer Strategy Behaviour
Issue:
Volume 2, Issue 4, August 2014
Pages:
78-84
Received:
23 July 2014
Accepted:
29 July 2014
Published:
10 August 2014
Abstract: It mainly focuses the consumer strategy behavior effect on retailers pricing mechanism. Under the condition of uncertainty demand and deterministic demand, consumers’ strategy behavior influence to price and profit. By introducing a discount factor, considering inventory timely complement and fixed inventory in two cases, obtains purchase decision and dynamic pricing strategies of consumers.
Abstract: It mainly focuses the consumer strategy behavior effect on retailers pricing mechanism. Under the condition of uncertainty demand and deterministic demand, consumers’ strategy behavior influence to price and profit. By introducing a discount factor, considering inventory timely complement and fixed inventory in two cases, obtains purchase decision ...
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Possibility of Compiling Results of Individual Trials under a Single Model
Issue:
Volume 2, Issue 4, August 2014
Pages:
85-90
Received:
10 July 2014
Accepted:
29 July 2014
Published:
10 August 2014
Abstract: The purpose of this work is to compile individual trials conducted at various locations and times in order to build and optimize a theoretical factorial model. A factorial plan is formed using planting time, plant density, nitrogen, phosphor and irrigation water data collected from trials conducted at Nazilli Cotton Research Station in 1966, 1967, 1971 and 1972. Using infinitesimal calculus theoretical combinations were formed, and individual and final R values were calculated. This was done by equalizing the different individual R values and levels belonging to independent variables. 1. Where the level numbers of the factors are non-recurrent (without frequency) and unequal; a) The level number of the factor with the largest level number should be accepted as the common level number. b) The individual (R) values total of the factor in question should be accepted as the final limit. c) The common individual (R) values total of the factor in question should be slightly lower than the final limit value. d) Individual (R) values calculated for each factor by finite infinitesimal calculus should be smaller than the largest individual (R) value of the factor in question. e) Finite infinitesimal calculus calculation should be started from the factor with the smallest level number. f) The largest valued total calculated on the factor in question and meeting the conditions in question (equalized R values totals and level numbers) should be accepted as the common total. 2. In case the level numbers of the factors consist of recurrent (with frequency) and non-recurrent (without frequency) groups, the calculations should be based on the group with the largest frequency. The operations defined under item 1 above shall also be applicable here. 3. In case the level numbers of the factors are non-recurrent (without frequency) and equal, the operations defined under item 1 above shall also be applicable here. The relative effects of the factors on the maximum yield level are given below: 25.224 % for planting time, 17.2245 % for plant density, 25.904 % for nitrogen, 13.904 % for phosphor, and 17.90 % for water. Here, five square squares of 5x5 are formed and 125 combinations are derived. Maximization was done by putting the individual R values with the largest final R value among the 125 combination in place in the formula R= -0.6080+ R_E+ R_B+ R_N+ R_P+ R_S , and maximum R value was calculated as R_max=752.110 kg/decare
Abstract: The purpose of this work is to compile individual trials conducted at various locations and times in order to build and optimize a theoretical factorial model. A factorial plan is formed using planting time, plant density, nitrogen, phosphor and irrigation water data collected from trials conducted at Nazilli Cotton Research Station in 1966, 1967, ...
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