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issuccessmtpma.m
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%Author: Zsolt T. Kosztyán Ph.D habil., University of Pannonia,
%Faculty of Economics, Department of Quantitative Methods
%----------------
%Feasibility check of traditional project management agent (APMa)
%----------------
%Output:
%Flag: %0=failed (infeasible for both sCONS and cCONS); 1=challanged
%(feasible for cCONS but infeasible for sCONS); 2=success (feasible for
%sCONS)
%----------------
%Inputs:
%PDM: N by N+(M-N)*W matrix of the stochastic project plan.
%PDM=[PEM,TD,CD{,QD}{,RD}], where PEM is an N by N upper triangular matrix
%of logic domain,
% TD is an N by w matrix of task durations,
% CD is an N by w matrix of cost demands,
%depends on the problem selection
% QD is an N by w matrix of quality parameters,
%depends on the resource allocation is performed or not
% RD is an N by w*nR matrix of resource demands.
%sCONS,cCONS: 3..3+nR+1 (depends on the problem selection) elements row vector of
%[Ct,Cc,{Cq,CR,}Cs] values, where
% Ct is the time constraint (max constraint, required in all problems)
% Cc is the cost constraint (max constraint, required in all problems)
% Cq is the quality constraint (min constraint, required in TQCTP problems))
% CR are the resource constraints (max constraint, required in
%resource-allocation problems)
% Cs is the score constraint (min constraint, required in all problems)
%Select: 1-18 scalar of problem selection
% 1: Select normal durations/cost demands
% 2: Select normal durations/cost demands/quality parameters
% 3: DTCTP: Discrete Time-Cost Trade-off Problem
% 4: CTCTP: Continouos Time-Cost Trade-off Problem
% 5: DTQCTP: Discrete Time-Quality-Cost Trade-off Problem
% 6: CTQCTP: Continouos Time-Quality-Cost Trade-off Problem
% 7: RCPSP: Resource-Constraint Project Scheduling Problem
% 8: PO-PSP: Pareto-Optimal resource-allocated Project Scheduling Problem
% 9: RC-DTCTP: Resource-Constraint Discrete Time-Cost Trade-off Problem
%10: RC-CTCTP: Resource-Constraint Continouos Time-Cost Trade-off Problem
%11: PO-DTCTP: Pareto-Optimal resource-allocated Discrete Time-Cost
%Trade-off Problem
%12: PO-CTCTP: Pareto-Optimal resource-allocated Continouos
%Time-Cost Trade-off Problem
%13: RC-PSPq: Resource-Constraint Project Scheduling Problem
%with quality parameters
%14: PO-PSPq: Pareto-Optimal resource-allocated Project Scheduling
%with quality parameters
%15: RC-DTCTP: Resource-Constraint Discrete Time-Quality-Cost
%Trade-off Problem
%16: PO-DTQCTP: Pareto-Optimal resource-allocated Discrete
%Time-Quality-Cost Trade-off Problem
%17: RC-CTQCTP: Resource-Constraint Continouos Time-Quality-Cost
%Trade-off Problem
%18: PO-CTQCTP: Pareto-Optimal resource-allocated Continouos
%Time-Quality-Cost Trade-off Problem
%typetfcn: Type of target function
% {0=maxTPQ,} 1=minTPT, 2=minTPC, 3=maxTPS, {4=minUF,} ~ composite
%w: Number of modes
%----------------
%Usage:
%Flag=issuccessmtpma(PDM,sCONS,cCONS,Select,typefcn,w)
%----------------
%Example:
%PDM=generatepdmq(30,0.05,0,20,30,20,2,2,2);
%Select=13;
%typefcn=999; %let target function be a composite target function
%w=3;
%Flag=issuccessmtpma(PDM,sCONS,cCONS,Select,typefcn,w)
%----------------
%Prepositions and Requirements:
%1.)The logic domian of the input PDM matrix must be an upper triangular
%matrix, where the matrix elements are between 0 to 1 interval.
%2.)Before running the evaluation, all matrix element (PEMi,j)of the
%original logic domain is converted to 0, if the PEMi,j<0.5, otherwise this
%element is converted to 1. It merans, if the score of inclusion (Pi,j) is
%greather than the score of exclusion (Qi,j). In this case the score value
%of the project scenario for converted matrix is highest.
%3.)The number of modes(w) is a positive integer. In case of countinous
%trade-off problems w=2 and in case of selections the w shuld be 1.
%4.)The number of resources (nR) is a positive number
%5.)The elements of Time/Cost/Quality/Resource Domains are positive real
%numbers.
%6.)Usually a monotonity are assumed, which, means: if tk,i<tk,j =>
%ck,i>=ck,j and qk,i<=qk,j, where 1<=k<=N is the k-th task, 1<=i,j<=w are
%the selected modes. This asumptation is only used in continous trade-off
%problems.
%7.)In the case of TPMa there is no flexible task dependency and uncertain
%task completions (see 2.), however, multiple modes are considered.
function Flag=issuccessmtpma(PDM,sCONS,cCONS,Select,typefcn,w)
Flag=0; %0=failed;1=challanged;2=success
PEM=PDM(:,1:size(PDM,1)); % N by N matrix of logic domain
P=PEM; % Initial N by N score matrix of task/dependency inclusion
Q=ones(size(PEM,1))-P; %Q=1-P
sCR=[]; %Resource constraints
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13)) %If quality
if numel(sCONS)>4 %paramters are considered
sCR=sCONS(4:end-1)'; %[Ct,Cc,Cq,CR',Cs]
end
else
if numel(sCONS)>3 %[Ct,Cc,CR',Cs]
sCR=sCONS(3:end-1)';
end
end
PSM=mtpma(PDM,sCONS,Select,typefcn,w); %Run PMa
N=size(PSM,1);
M=size(PSM,2);
DSM=PSM(:,1:size(PSM,1));
TD=PSM(:,size(PSM,1)+1);
CD=PSM(:,size(PSM,1)+2);
QD=[];
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
QD=PSM(:,size(PSM,1)+3);
end
SST=PSM(:,end);
RD=[];
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
if M>N+4
RD=PSM(:,size(PSM,1)+4:end-1);
end
else
if M>N+3
RD=PSM(:,size(PSM,1)+3:end-1);
end
end
scons=sCONS; %If quality parameter is considered...
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
if numel(sCR)>0 %If resources are considered
scons(3)=-sCONS(3); %Cq is maximal constraint
scons(end)=-sCONS(end); %Cs is maximal constraint
sC=min(scons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
-tpqfast(DSM,P,QD),maxresfun(SST,DSM,TD,RD)',...
-maxscore_PEM(DSM,P,Q)]);
else
scons(3)=-sCONS(3); %Cq is maximal constraint
scons(end)=-sCONS(end); %Cs is maximal constraint
sC=min(scons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
-tpqfast(DSM,P,QD),...
-maxscore_PEM(DSM,P,Q)]);
end
else
if numel(sCR)>0 %If resources are considered
scons(end)=-sCONS(end); %Cs is maximal constraint
sC=min(scons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
maxresfun(SST,DSM,TD,RD)',-maxscore_PEM(DSM,P,Q)]);
else
scons(end)=-sCONS(end); %Cs is maximal constraint
sC=min(scons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
-maxscore_PEM(DSM,P,Q)]);
end
end
if (sC>=0)
Flag=2; %Success
else
PSM=mtpma(PDM,cCONS,Select,typefcn,w); %Run PMa for relaxed constraint
N=size(PSM,1);
M=size(PSM,2);
DSM=PSM(:,1:size(PSM,1));
TD=PSM(:,size(PSM,1)+1);
CD=PSM(:,size(PSM,1)+2);
QD=[];
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
QD=PSM(:,size(PSM,1)+3);
end
SST=PSM(:,end);
RD=[];
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
if M>N+4
RD=PSM(:,size(PSM,1)+4:end-1);
end
else
if M>N+3
RD=PSM(:,size(PSM,1)+3:end-1);
end
end
ccons=cCONS; %If quality parameter is considered...
if ((Select==2)||(Select==5)||(Select==6)||(Select>=13))
if numel(sCR)>0 %If resources are considered
ccons(3)=-cCONS(3); %Cq is maximal constraint
ccons(end)=-cCONS(end); %Cs is maximal constraint
cC=min(ccons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
-tpqfast(DSM,P,QD),maxresfun(SST,DSM,TD,RD)',...
-maxscore_PEM(DSM,P,Q)]);
else
ccons(3)=-cCONS(3); %Cq is maximal constraint
ccons(end)=-cCONS(end); %Cs is maximal constraint
cC=min(ccons-[tptfast(DSM,TD),tpcfast(DSM,CD),...
-tpqfast(DSM,P,QD),...
-maxscore_PEM(DSM,P,Q)]);
end
else
if numel(sCR)>0
ccons(end)=-cCONS(end); %Cs is maximal constraint
cC=min(ccons-...
[tptfast(DSM,TD),tpcfast(DSM,CD),...
maxresfun(SST,DSM,TD,RD)',...
-maxscore_PEM(DSM,P,Q)]);
else
ccons(end)=-cCONS(end); %Cs is maximal constraint
cC=min(ccons-...
[tptfast(DSM,TD),tpcfast(DSM,CD),...
-maxscore_PEM(DSM,P,Q)]);
end
end
if (cC>=0)
Flag=1; %Challenged
end
end