a bi objective minimum cost-time network flow problem
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A Bi-Objective Minimum Cost-Time Network Flow Problem
Amirhadi Zakeri
گاه آزاد )'&ان #"ی دا0ش
Islamic Azad University Tehran Central
Dr. Mehrdad Mehrbod
Amirhadi Zakeri
ID: 940224828
Abstract The Minimum Cost-Time Network Flow (MCTNF) problem deals with shipping the available supply through the directed network to satisfy demand at minimal total cost and minimal total time. Shipping cost is dependent on the value of flow on the arcs; however shipping time is a fixed time of using an arc to send flow. In this paper, a new Bi-Objective Minimum Cost-Time Flow (BOMCTF) problem is formulated. The first and second objective functions consider the total shipping cost and the total shipping fixed time, respectively. We utilize the weighted sum scalarization technique to convert the proposed model to a well- known fixed charge minimum cost flow problem with single objective function. This problem is a parametric mixed integer programming which can be solved by the existence methods. A numerical example is taken to illustrate the proposed approach.
©20154ThheeAAuuththoorsr.s.PPubulbislihsehdedbybyElEselsveievrieBr.BV.VT.his is an open access article under the CC BY-NC-ND license (Shettlpe:c/t/icorenaatinvde/copmeemr-orenvs.ioerwg/ulincednesrerse/sbpyo-ncs-inbdil/i4ty.0o/)f. Academic World Research and Education Center. Selection and/ peer-review under responsibility of Academic World Research and Education Center
مساله حداقل هزینه-زمان(MCTNF)
Minimum Cost-Time Network Flow
Bi-Objective
directed network to satisfy demand at minimal total cost and minimal total timeگراف جھتدار
A Bcost
shipping cost
shipping time is a fixed time of using an arc to send flow
First total shipping cost
Second total shipping fixed time{objectives
A B( c , t , u )ij ij ij
MCF BOMCTF weighted sum scalarization technique
Bi- objective One objective
تکنیک مجموع اوزان
MCF
MCCF
MCIF
MCF with Continuous flows
MCF with Integer flows
variables are real valued variables
variables restricted to integer values
1. Introduction
متغیرهای حقیقی
مقادیر عدد صحیح
In this paper, we formulate and solve a new BOMCF problem, named Bi-Objective Minimum Cost-Time Flow
Main difference direct dependence of the decision variables of the
objectives
وابستگی مستقیم متغیرهای تصمیم گیری اهداف
flow conservation
capacity constraints محدودیت ظرفیت
حفظ جریان
In addition to the flow variables, new binary variables dependent on the flow variables are also present
+
G=(N,A) directed network
cost= c
fixed time = tcapacity= u
ij
ij
ij
هزینه
زمان ثابت
ظرفیت کمان
i ∈ N(i,j) ∈ A
b =indicates its supply or demand depending i
b =0 ⇾ node is a transshipment node i
bi-objective model:
auxiliary binary variable y is utilized to consider time t for positive flow xij ij ij real valued variables,
Multi-Objective Optimization (MOO) problems
cannot improve some objectives without sacrificing others
non-dominated points
Efficient solutions and their associated points in the objectives space
=
supported solution the optimal solution of a model with weighted sum scalarization objective function non-supported solution
S = the set of all feasible solutions of the problem
Z = the feasible set in objective space
≠
Definition 1.
if and then it is called dominate in decision space
dominate in decision space
Definition 2. a feasible solution is called efficient, or Pareto optimal, if such that dominates
If is an efficient solution
Vector non-dominated point in the objective space
The set of efficient solutions
the image of in is called the non-dominated
Definition 3. An efficient solution is a supported efficient solution, if it is an optimal solution of the following weighted sum single objective problem
for some . If is a supported efficient solution, then is named a supported non- dominated point.
∈ (0,1)
Definition 4. An efficient solution is a non-supported efficient solution, if there are no positive values and such that is an optimal solution of the model (2).
2
supported non-
dominated
in the objective space
non-supported
non-dominated
dominated point
its associated feasible solution is inefficient
Solving BOMCTF Problem
BOMCTF problem are classified into supported
non- supported
Finding all supported and non-supported efficient solutions
Major challenge
{ A supported solution is the optimal solution of the model (2)
correlation between and conditional constraint
To resolve this difficulty we replace constraint (1.e) with two auxiliary linear constraints, and reformulate the model (1)
همبستگی محدودیت شرطی
Solving BOMCTF Problem
M is a sufficiently large positive number
Solving BOMCTF Problem
M is a sufficiently large positive number
Solving BOMCTF Problem
M is a sufficiently large positive number
is redundant
is redundant
We formulate the following parametric problem to produce a set of supported efficient solutions of the above problem:
Note that the objective function helps us to ignore the constraints
A B( c , t , u )ij ij ij
A B( c , t , u )ij ij ij
Million Rials
Hour
Million tonsCapacity
Cost
Fixed time
b = the value of supply or demand (in terms of million tons) i
each city is considered as a node For each route For each city there is a b scalar which indicates the value of supply or demand
S : producing a specific good Others are consumers.
13.5 million tons of goods through the network to satisfy demand at minimal cost and time.
we apply the model (4) for the given data set in Fig 2
There are two alternative solutions for all . The first supported efficient solution (let for instance =0.05 ) is as bellow:
The related total shipping cost and fixed time is 1270.9 and 66, respectively.
∈ (0,1)
The next supported efficient solution can be obtained by solving the model (4) for (as an instance =0.5 ):
The total shipping cost and fixed time for this solution is 1242.5 and 77, respectively
As a result, two supported efficient solutions are achieved by applying the suggested approach.
proposed approach succeed in finding all supported efficient solution
It fails to determine unsupported efficient solutions
END