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Layout and DesignKapitel 4 / 1 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) common mathematical formulation for intra-company location.

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Presentation on theme: "Layout and DesignKapitel 4 / 1 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) common mathematical formulation for intra-company location."— Presentation transcript:

1 Layout and DesignKapitel 4 / 1 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) common mathematical formulation for intra-company location problems cost of an assignment is determined by the distances and the material flows between all given entities each assignment decision has direct impact on the decision referring to all other objects

2 Layout and DesignKapitel 4 / 2 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Activity relationship charts: graphical means of representing the desirability of locating pairs of machines/operations near to each other common letter codes for classification of closeness ratings: AAbsolutely necessary. Because two machines/operations use the same equipment or facilities, they must be located near each other. EEspecially important. The facilities may for example require the same personnel or records. IImportant. The activities may be located in sequence in the normal work flow. Nahmias, S.: Production and Operations Analysis, 4th ed., McGraw-Hill, 2000, Chapter 10

3 Layout and DesignKapitel 4 / 3 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) common letter codes for classification of closeness ratings: OOrdinary importance. It would be convenient to have the facilities near each other, but it is not essential. UUnimportant. It does not matter whether the facilities are located near each other or not. XUndesirable. Locating a wedding department near one that uses flammable liquids would be an example of this category. In the original conception of the QAP a number giving the reason for each closeness rating is needed as well. In case of closeness rating X a negative value would be used to indicate the undesirability of closeness for the according machines/operations. Nahmias, S.: Production and Operations Analysis, 4th ed., McGraw-Hill, 2000, Chapter 10

4 Layout and DesignKapitel 4 / 4 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Example: Met Me, Inc., is a franchised chain of fast-food hamburger restaurants. A new restaurant is being located in a growing suburban community near Reston, Virginia. Each restaurant has the following departments: 1.Cooking burgers 2.Cooking fries 3.Packing and storing burgers 4.Drink dispensers 5.Counter servers 6.Drive-up server Nahmias, S.: Production and Operations Analysis, 4th ed., McGraw-Hill, 2000, Chapter 10

5 Layout and DesignKapitel 4 / 5 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Nahmias, S.: Production and Operations Analysis, 4th ed., McGraw-Hill, 2000, Chapter 10 Activity relationship diagram for the example problem:

6 Layout and DesignKapitel 4 / 6 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Mathematical formulation: we need both distances between the locations and material flow between organizational entities (OE) n organizational entities (OE), all of them are of same size and can therefore be interchanged with each other n locations, each of which can be provided withe each of the OE (exactly 1) t hi... transp. intensity, i.e. material flow between OE h and OE i d jk... distance between j and location k (not implicitly symmetric) Transportation costs are proportional to transported amount and distance.

7 Layout and DesignKapitel 4 / 7 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) If OE h is assigned to location j and OE i to location k the transportation cost per unit transported from OE h to OE i is determined by d jk we determine the total transportation cost by multiplying d jk with the material flow between OE h zu OE i which is t hi j k... locations h i... OE d jk. t hi. Cost = t hi d jk

8 Layout and DesignKapitel 4 / 8 (c) Prof. Richard F. Hartl Similar to the LAP: binary decision variables If OE h location j ( x hj = 1 ) and OE i location k ( x ik = 1 ) Transportation cost per unit transported from OE h to OE i : Total transportation cost: The Quadratic Assignment Problem (QAP) j k... locations h i... OE d jk. t hi. Cost = t hi d jk x hj = 1 x ik = 1

9 Layout and DesignKapitel 4 / 9 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Objective: Minimize the total transportation costs between all OE Constraints für h = 1,..., n... each OE h assigned to exactly 1 location j für j = 1,..., n... each location j is provided with exactly 1 OE h = 0 or 1... binary decision variable Similar to LAP!!! Quadratic function QAP

10 Layout and DesignKapitel 4 / 10 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Example: Calculate cost for 3 OE (1,2,3) and 3 locations (A, B, C) A BC Distances between locations d jk Material flow t hi 1 possible solution: 1 A, 2 B, 3 C, i.e. x 1A = 1, x 2B = 1, x 3C = 1, all other x ij = 0 All constraints are fulfilled. Total transportation cost: 0*0 + 1*1 + 2*1 + 1*2 + 0*0 + 1*2 + 3*3 + 1*1 + 0*0 = 17

11 Layout and DesignKapitel 4 / 11 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) This solution is not optimal since OE 1 and 3 (which have a high degree of material flow) are assigned to locations A and C (which have the highest distance between them). A better solution would be.: 1 C, 2 A and 3 B, i.e. x 1C = 1, x 2A = 1, x 3B = 1. with total transportation cost: 0*0 + 3*1 + 1*1 + 2*2 + 0*0 + 2*1 + 1*3 + 1*1 + 0*0 = 14 2 A 3 B1 C Distances Material flow

12 Layout and DesignKapitel 4 / 12 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) We resorted the matrix such that row and columns appear the following sequence 1 C, 2 A and 3 B, i.e C, A, B (it is advisable to perform the resorting in 2 steps: first rows than columns or the other way round)

13 Layout and DesignKapitel 4 / 13 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Starting heuristics: refer to the combination of one of the following possibilities to select an OE and a location. the core is defined by the already chosen OE After each iteration another OE is added to the core due to one of the following priorities

14 Layout and DesignKapitel 4 / 14 (c) Prof. Richard F. Hartl 1.Selection of (non-assigned) OE A1those having the maximum sum of material flow to all (other) OE A2a) those having the maximum material flow to the last- assigned OE b) those having the maximum material flow to an assigned OE A3those having the maximum material flow to all assigned OE (core) A4random choice

15 Layout and DesignKapitel 4 / 15 (c) Prof. Richard F. Hartl 1.Selection of (non-assigned) locations B1those having the minimum total distance to all other locations B2those being neighbouring to the last-chosen location B3a) those leading to the minimum sum of transportation cost to the core b) like a) but furthermore we try to exchange the location with neigboured OE c) a location (empty or allocated) such that the sum of transportation costs within the new core is minimized (in case an allocated location is selected, the displaced OE is assigned to an empty location) B4random choice

16 Layout and DesignKapitel 4 / 16 (c) Prof. Richard F. Hartl Example Combination of A1 and B1: Arrange all OE according to decreasing sum of material flow Arrange all locations according to increasing distance to all other locations Manhatten-distance between locations. (matrix is symmetric -> consideration of the matrix triangle is sufficient) ABC DEF GHI

17 Layout and DesignKapitel 4 / 17 (c) Prof. Richard F. Hartl Example – Material flow OE123456789 1----3---- 2 -312-4-- -352-34 4 ---1-- 5 -221- 6 ---- 7 --- 8 -- 9 - 3 10 20 5 15 4 7 4 4 3 Sequence of OE (according to decreasing material flow): 3, 5, 2, 7, 4, 6, 8, 9, 1 Sum of material flow between 1 5 and 5 1

18 Layout and DesignKapitel 4 / 18 (c) Prof. Richard F. Hartl Example - Distances LABCDEFGHI A-12123234 B -1212323 C -321432 D -12123 -1212 F -321 G -12 H -1 I - 18 15 18 15 12 15 18 15 18 E Sequence of locations (according to increasing distances): E, B, D, F, H, A, C, G, I

19 Layout and DesignKapitel 4 / 19 (c) Prof. Richard F. Hartl Sequence of OE: 3, 5, 2, 7, 4, 6, 8, 9, 1 Sequence of locations: E, B, D, F, H, A, C, G, I Assignment: Example - Assignment OE123456789 Loc.IDEHBAFCG

20 Layout and DesignKapitel 4 / 20 (c) Prof. Richard F. Hartl Example – Total costs OE123456789 1----3*3---- 2 -3*11*22*2-4*2-- 3 -3*15*12*2-3*24*2 4 ---1*2-- 5 -2*12*21*1- 6 ---- 7 --- 8 -- 9 - OE 1 and 5 are assigned to locations I and B 3 (Distance 1-5) * 3 (Flow I-B) Total cost = 61

21 Layout and DesignKapitel 4 / 21 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Improvement heuristics: Try to improve solutions by exchanging OE-pairs (see the introducing example) Check if the exchange of locations of 2 OE reduces costs. Exchange of OE-triples only if computational time is acceptable. There are a number of possibilities to determine OE-pairs (which should be checked for an exchange of locations):

22 Layout and DesignKapitel 4 / 22 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Selection of pairs for potential exchanges: C1all n(n - 1)/2 pairs C2a subset of pairs C3random choice Selection of pairs which finally are exchanged: D1that pair whose exchange of locations leads to the highest cost reduction. (best pair) D2the first pair whose exchange of locations leads to a cost reduction (first pair)

23 Layout and DesignKapitel 4 / 23 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Solution quality Combination of C1 and D1: Quite high degree of computational effort. Relatively good solution quality A common method is to start with C1 and skip to D1 as soon as the solution is reasonably good. Combination of C1 and D1 is the equivalent to 2-opt method for the TSP CRAFT : Well-known (heuristic) solution method For problems where OE are of similar size CRAFT equals a combination of C1 and D1

24 Layout and DesignKapitel 4 / 24 (c) Prof. Richard F. Hartl The Quadratic Assignment Problem (QAP) Random Choice (C3 and D2): Quite good results the fact that sometimes the best exchange of all exchanges which have been checked leads to an increase of costs is no disadvantage, because it reduces the risk to be trapped in local optima The basic idea and several adaptions/combinations of A, B, C, and D are discussed in literature

25 Layout and DesignKapitel 4 / 25 (c) Prof. Richard F. Hartl Umlaufmethode Heurisitic method Combination of starting and improvement heuristics Components: Initialization (i = 1): Those OE having the maximum sum of material flow [A1] is assigned to the centre of locations (i.e. the location having the minimum sum of distances to all other locations [B1]). Iteration i (i = 2,..., n): assign OE i

26 Layout and DesignKapitel 4 / 26 (c) Prof. Richard F. Hartl Umlaufmethode Part 1: Selection of OE and of free location: select those OE with the maximum sum of material flow to all OE assigned to the core [A3] assign the selected OE to a free location so that the sum of transportation costs to the core (within the core) is minimized [B3a]

27 Layout and DesignKapitel 4 / 27 (c) Prof. Richard F. Hartl Umlaufmethode Part 2: Improvement step in iteration i = 4: check pair wise exchanges of the last-assigned OE with all other OE in the core [C2]wenn eine Verbesserung gefunden ist, führe diese Änderung durch und beginne wieder mit Teil 2 [D2] if an improvement is found, the exchange is conducted and we start again with Part 2 [D2]

28 Layout and DesignKapitel 4 / 28 (c) Prof. Richard F. Hartl Example – Part 1 Initialization (i = 1): E = centre Assign OE 3 to centre. ABC DE 3F GHI

29 Layout and DesignKapitel 4 / 29 (c) Prof. Richard F. Hartl Sequence of assignment i =123456789 OE3 10 23 3 43 55 62 70 83 94 5 3 2 0 2 2 1 0 0 00 00 0 0 0 0 00 0 000 0 00 11 4 2 7 4 68 9 1 i = 1: assign 3 first i = 5 ii = 2: 5 highest mat.flow to 3 i = 9 ii = 3: 2 highest mat.flow to core (3,5) i = 6 ii = 4 i = 7 i = 8

30 Layout and DesignKapitel 4 / 30 (c) Prof. Richard F. Hartl Example – PArt 1 Iteration i = 2 Iteration The maximum material flow to OE 3 is from OE 5 Distances d BE = d DE = d FE = d HE = 1 equally minimal select D, In iteration i = 2 OE 5 is assigned to D-5. ABC D 5E 3F GHI

31 Layout and DesignKapitel 4 / 31 (c) Prof. Richard F. Hartl Example – Part 1 Iteration i = 3 Iteration The maximum material flow to the core (3,5) is from OE 2 Select location X, such that d XE t 23 + d XD t 25 = d XE 3 + d XD 2 is minimal: (A, B, G od. H) X = Ad AE 3 + d AD 2 = 2 3 + 1 2 = 8 X = Bd BE 3 + d BD 2 = 1 3 + 2 2 = 7 X = Fd FE 3 + d FD 2 = 1 3 + 2 2 = 7 X = Gd GE 3 + d GD 2 = 2 3 + 1 2 = 8 X = Hd HE 3 + d HD 2 = 1 3 + 2 2 = 7 B, F or H B is selected In iteration i = 3 we assign OE to B AB 2C D 5E 3F GHI

32 Layout and DesignKapitel 4 / 32 (c) Prof. Richard F. Hartl Example – Part 1 Iteration i = 4 Iteration The maximum material flow to the core (2,3,5) is from OE 7 (2, 3, 5) Select location X, such thath d XE t 73 + d XD t 75 + d XB t 72 = d XE 0 + d XD 2 + d XB 4 is minimal according to the given map -> A is the best choice In iteration i = 4 we tentatively assign OE 7 to location A

33 Layout and DesignKapitel 4 / 33 (c) Prof. Richard F. Hartl Example – Part 2 Try to exchange A with E, B or D and calculate the according costs: Original assignement (Part 1): E-3, D-5, B-2, A-7Cost =1 5+1 3+2 0+2 2+1 2+1 4 = 18 tryE-3, D-5, A-2, B-7 Cost = 1 5+2 3+1 0+1 2+2 2+1 4 = 21 tryE-3, A-5, B-2, D-7 Cost = 2 5+1 3+1 0+1 2+1 2+2 4 = 25 tryA-3, D-5, B-2, E-7 Cost = 1 5+1 3+2 0+2 2+1 2+1 4 = 18 Exchanging A with E would be possible but does not lead to a reduction of costs. Thus, we do not perform any exchange but go on with the solution determined in part 1…and so on…

34 Layout and DesignKapitel 4 / 34 (c) Prof. Richard F. Hartl Example – Part 2 After 8 iterations without part 2: Cost = 54 With part 2 (last-assigned OE (9) is to be exchanged with OE 4): Cost = 51 While a manual calculation of larger problems is obviously quite time consuming an implementation and therefore computerized calculation is relatively simple


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