Transportation Polytopes: a Twenty year Update


 Briana Reed
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1 Transportation Polytopes: a Twenty year Update Jesús Antonio De Loera University of California, Davis Based on various papers joint with R. Hemmecke, E.Kim, F. Liu, U. Rothblum, F. Santos, S. Onn, R. Yoshida, R. Weismantel SUPPLIES BY FACTORIES DEMANDS ON FOUR CITIES
2 Goal and Plan of this Lecture: Transportation polytopes arise in Optimization, Statistics and pure Mathematics! Go back to the beginning of Mathematical Programming: Kantorovich and Koopmans already studied them in the 93 s. Two prior extended surveys and open problem collections: 966 by Klee Witzgall and 984 by KovalevYemelichevKratsov: TODAY: a new updated survey about transportation polytopes, with many new results, open questions... Part I: What is a transportation polytope? Part II: Classical TwoWay Transportation Polytopes Part III: Multiway Transportation Polytopes Part IV: Open Problems 2
3 Part : WHAT IS A TRANSPORTATION POLYTOPE?? 3
4 CLASSICAL (n m)transportation Polytopes:???????????????? The 2way transportation polytope is the set of all possible tables whose row/column sums equal the given margins. 4
5 MultiWay Transportation Polytopes. A dway table is an n n 2 n d array of nonnegative real numbers v = (v i,...,i d ), i j n j. For m < d, an mmargin of v is any of the possible mtables obtained by summing the entries over all but m indices. Example If (v i,j,k ) is a 3table then its margin is v +,+,+ = n n2 n3 i= j= k= v i,j,k, its margins are (v i,+,+ ) = ( n 2 n3 j= k= v i,j,k) and likewise (v +,j,+ ), (v +,+,k ), and its 2margins are (v i,j,+ ) = ( n 3 k= v i,j,k) and likewise (v i,+,k ), (v +,j,k ). Definition: A multiindex transportation polytope is the set of all real dtables that satisfy a set of given margins. Definition An Assignment polytope is when all right handside margins have entry value one. (They also receive the names Birkhoffvon Neumann polytopes or Polytope of polystochastic matrices. 5
6 EXAMPLE k i j 6
7 EXAMPLE
8 EXAMPLE 3 8
9 Part 2: TWOWAY TRANSPORTATION POLYTOPES 9
10 Constraint Matrix has SPECIAL shape We can easily see that the system Ax = b, x has as constraint matrix A the vertexedge incidence matrix of the complete bipartite graph K n,m. Example: For the transportation problem????????????????
11 we have A =
12 Background facts: We know a lot! Theorem: In the classical n m transportation polytope we are given marginals a = (a,...,a n ) and b = (b,...,b m ), () (dimension and feasibility) If a i = b i, then polytope is nonempty and it has dimension (n )(m ). The northwestcorner Rule can find a solution! (2) (vertices and lattice points) Given integral consistent marginals a, b, all vertices of the corresponding transportation polytope are integral. Constraint matrix is totally unimodular! Proposition 2way transportation polytopes have the integral interval property for all entries: If l < x ij < u, then there is a lattice point with x ij = s for all integers in between l, u. No gaps! (3) (optimization) All Integer linear programs can be solved efficiently. 2
13 Graphs of twoway transportation polytopes Theorem: Let X = (x ij ) be a matrix that belongs to the n m transportation polytope T(a,b). Create the auxiliary graph F X with n m nodes and edge {(i, j) : x i,j > }. Then the matrix X is a vertex of the transportation polytope T(a,b) if and only if F X forms a spanning forest in the complete bipartite graph K n,m. Lemma:(Adjacency conditions of vertices) Let X and Y be distinct vertices of the transportation polytope T(a,b). The vertices are adjacent if and only if the union of the associated graphs F X and F Y contains a unique cycle. Theorem:(24 Brightwellvan den HeuvelStougie) The diameter of the transportation polytope of size n m does not exceed 8(m + n 2). breaking news: (28 Edward Kim) The diameter is less than or equal to 3(m + n 2). 3
14 Part 3: MULTIWAY TRANSPORTATION POLYTOPES 4
15 Several Open Questions from the 98 s answered () Real feasibility and Dimension: (Vlach Problems 986): Do the conditions on the Several conditions on the margins proposed by Schell, Haley, Moravek and Vlack during the 98 s. Do they suffice to guarantee that the 2margin 3way Transportation polytope is nonempty? NO! These conditions are necessary but not sufficient But, is there some easy way to find a feasible solution in terms of the 2margins of those 3way transportation polytopes which are empty? Something like the northwestcorner rule??? Unlikely, as hard a solving an arbitrary LP!!!! What is the dimension of the polytope? 5
16 Dimension can be any number from up to (n )(m )(k ) () Integer Feasibility Problems: Given integral 2margins, that describe a 3transportation polytope, is there an integer table with these margins? can one such integral dtable be efficiently determined? NO, problem is NPcomplete already for 3 n m transportation polytopes Do kway tables have the integral interval property for entry values? No, any set of nonnegative integers can be the values of a given entry! There are Gaps! (3) The graphs of 2margin kway transportation polytopes Is there a nice easy characterization of vertices and edges? Do we have a good bound for the diameter? This problem is as hard as proving a bound for ALL polytopes!!! 6
17 A UNIVERSALITY THEOREM Theorem: (JD & S. Onn 24) Any rational polytope P = {y R n : Ay = b y } is polynomialtime representable as a 3way (r c 3) transportation polytope { x R r c 3 : x i,j,k = w j,k, j i x i,j,k = v i,k, k x i,j,k = u i,j }. The polytope P R p is representable as a polytope T R q if there is an injection σ : {,...,p} {,...,q} such that the projection π : R q R p : x = (x,...,x q ) π(x) = (x σ(),...,x σ(p) ) is a bijection between T and P and between the sets of integer points T Z q and P Z p. 7
18 Theorem (JD & S. Onn)(now with complexity estimate). Any polytope P = {y R n :Ay = b} with integer m n matrix A = (a i,j ) and integer b is polynomialtime representable as a slim transportation polytope T = { x R r c 3 : i x i,j,k = w j,k, j x i,j,k = v i,k, k x i,j,k = u i,j }, with r = O(m 2 (n + L) 2 ) rows and c = O(m(n + L)) columns, where L := n j= maxm i= log 2 a i,j. 8
19 Three Independent Steps Step Reduce Size of Coefficients: Step 2 Encode polytope INTO transportation polytope with margins with some entries bounded Step 3 Encode any transportation polytope with margins and bounded entries INTO transportation polytope with 2margins 9
20 Step Given P = {y : Ay = b} where A = (a i,j ) is an integer matrix and b is an integer vector. We represent it as a polytope Q = {x : Cx = d}, in polynomialtime, with a {,,, 2}valued matrix C = (c i,j ) of coefficients. Use the binary expansion a i,j = k j s= t s2 s with all t s {,}, we rewrite this term as ± k j s= t sx j,s. EXAMPLE: The equation 3y 5y 2 + 2y 3 = 7 becomes 2x, x, = 2x 2, x 2, = 2x 2, x 2,2 = 2x 3, x 3, = x, +x, x 2, x 2,2 +x 3, = 7. 2
21 Step 2 Each equation k =,...,m will be encoded in a horizontal table plus an extra layer of slacks. Each variable y j, j =,...,n will be encoded in a vertical box Other entries are zero. 2
22 EXAMPLE Starting one dimensional polytope P = {y 2y =, y } we obtain INPUT table size (2,2,2) marginals = OUTPUT table size (3,4,6) 2 marginals (see below) entry upper bounds ( see below) Unique real feasible array Unique real feasible array All entries = /2 or All entries /2 and No integer table No integer table. 22
23 MORE CONSEQUENCES (3) All linear and integer programming problems are Slim 3way Transportation Problems. Any linear or integer programming problem is equivalent to one that has only {, }valued coefficients, with exactly three s per column, and depends only on the righthand side data. (4) Problem reduction If there is an polynomialtime algorithm for 3way transportation problems would imply the existence of a polynomialtime algorithm for linear programs in general. For example, if a polynomial diameter is true for 3way transportation polytopes given by 2marginals, then it is true for all rational polytopes! (5) Hardness of approximation The family of 3way transportation problems of (r, c, 3) and specified by 2margins contains subproblems that admit fully polynomial approximation schemes as well as subproblems that do not have arbitrarily close approximation (unless NP = P). 23
24 kway margin transportation problems Theorem: (JD & S. Onn 24) Any rational polytope P = {y R n : Ay = b, y } is polynomialtime representable as a face of a 3way (r c 3) transportation polytope with margins T = { x R r c 3 u j }. : i,j x i,j,k = w k, j,k x i,j,k = v i, i,k x i,j,k = Theorem: [JD, E. Kim, F. Santos, S. Onn 27] Any 3way transportation polytope of size l m n with fixed margins has diameter no more than 8(l + m + n) 2. Question: Can one bound the diameter of a face of the margin transportation polytope?? 24
25 kway margin Assignment polytopes are Nasty too!! Theorem: (Karp 972) The optimization problems maximize/minimize p i,j,k x i,j,k subject to { x Z n n n : are NPhard. i,j x i,j,k =, j,k x i,j,k =, i,k x i,j,k = }. Theorem: (CramaSpieksma 992) For the minimization case, no polynomial time algorithm can even achieve a constant performance ratio unless NP=P. Theorem (Gromova 992) Any positive decreasing vector v with components less than one is a permutation of part of a vertex of some 3way assignment polytope. 25
26 New Positive Results Theorem (JDL, Hemmecke, Onn, Weismantel) Fix any r,s. Then there is a polynomial time algorithm that, given l, integer objective vector c, and integer linesums (u i,j ), (v i,k ) and (w j,k ), solves the integer transportation problem min{ cx : x N r s l, i x i,j,k = w j,k, j x i,j,k = v i,k, k x i,j,k = u i,j }. Theorem 2 (JDL, Hemmecke, Onn, Rothblum, Weismantel) Let d, r, s be fixed positive integers. Given integer linesums margins tables (u i,j ), (v i,k ) and (w j,k ), arrays w,...,w d N r s l, and a convex function c : R d R, presented by comparison oracle, then 26
27 there is a polynomial oracletime algorithm that, solves the convex maximization integer 3way transportation problem max c(w x,...,w d x) subject to { x N r s l, i x i,j,k = w j,k, j x i,j,k = v i,k, k x i,j,k = u i,j }. HemmeckeOnnWeismantel (27) proved now (using algebra again!) that convex minimization can be also done efficiently 27
28 What is behind these theorems? Algebra + Graver Test Sets!! Closely related to Commutative Algebra! The lattice L(A) = {x Z n : Ax = } has a natural partial order. For u,v Z n we say that u is conformal to v, denoted u v, if u i v i and u i v i for i =,...,n, that is, u and v lie in the same orthant of R n and each component of u is bounded by the corresponding component of v in absolute value. The Graver basis of an integer matrix A is the set of conformalminimal nonzero integer dependencies on A. Example: If A = [ 2 ] then its Graver basis is. ±{[2,,], [,, 2],[,, ], [,, ]} 28
29 Theorem [J. Graver 975] Graver bases for A can be used to solve the augmentation problem. Given A Z m n, x N n and c Z n, either find an improving direction g Z n, namely one with x g {y N n : Ay = Ax} and cg >, or assert that no such g exists. 29
30 For a fixed cost vector c, visualize a Graver basis of of an integer program by creating a graph!! Key ingredient [SchulzWeismantel] The number of directed augmentation steps needed to reach optimality is polynomially bounded. 3
31 Part 4: SOME OPEN PROBLEMS 3
32 Open Question: Determine the exact value for the volume of the n n Birkhoff polytope B n. Can this volume be computed efficiently? For general polytopes volume computation is a #Phard problem! Recently, R. Canfield and B. Mckay gave a rather good asymptotic value for the volume of the Birkhoff polytope. Also recently, we (joint with F. Liu and R. Yoshida) provided an exact formula for the volume of B n. Open Question: What are the possible number of vertices of simple m n transportation polytopes? 32
33 sizes Distribution of number of vertices in transportation polytopes We have a complete classification of all combinatorial types of simple n m transportation polytopes. 5 5 is the smallest value for which we do not know all types yet! We used the theory of regular triangulations (GelfandKapranovZelevinsky). 33
34 Open Question: What is the distribution of number of vertices for m n k nondegenerate 3way transportation polytopes, specified by 2margin matrices A, B,C? Conjecture: All integer numbers between and m + n, and only these, are realized as the diameters of m n transportation polytopes. Conjecture: Are all graphs of n m transportation polytopes hamiltonian. Theorem:(Bolker 972) When n, m are relatively prime, the maximum possible number of vertices on an m n transportation polytopes is achieved by the central transportation polytope whose marginals are the mvector a = (n,n,...,n) and nvector b = (m, m,...,m). Open Question: What is the largest possible number of vertices in a 3way n m k transportation polytope? 34
35 The YKK conjecture The m n k generalized central transportation polytope is the 3way transportation polytope of line sums whose 2 margins are given by the n k matrix U(j,k) = m, the m k matrix V (i, k) = n, and the m n matrix W(i, j) = k. Conjecture: (YemelichevKovalevKratsov) The generalized central transportation polytope has the largest number of vertices among 3 way transportation polytopes. FALSE!! (JD, E. Kim, F. Santos, S. Onn) 35
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