2-approximation algorithm for minmax absolute maximum lateness scheduling-location problem

The problem of minmax absolute scheduling-location is investigated on trees with interval edge length. Jobs are located at vertices and must travel to the machine. The goal is to find a machine location and simultaneously a schedule to minimize the maximum lateness in the worst-case. We derive a result that could reduce the robust versions to deterministic problems. An efficient algorithm is developed to solve special cases. A 2-approximation algorithm is proposed for the robust problem on the underlying tree.     

A 3-approximation algorithm for two-dimensional bin packing

In the classical two-dimensional bin packing problem one is asked to pack a set of rectangular items, without overlap and without any rotation, into the minimum number of identical square bins. We give an approximation algorithm with absolute worst-case ratio of 3.     

A 2-approximation algorithm for the network substitution problem

The network substitution problem is to substitute an existing network for a new network so that to minimize the cost of exploiting the existing network during the period when the new network is being constructed. We show that this problem is NP-hard, and propose a 2-approximation algorithm for solving it.     

A better approximation algorithm for the budget prize collecting tree problem

Given an undirected graph G=(V,E), an edge cost c(e)?0 for each edge e∈E, a vertex prize p(v)?0 for each vertex v∈V, and an edge budget B. The BUDGET PRIZE COLLECTING TREE PROBLEM is to find a subtree T′=(V′,E′) that maximizes , subject to . We present a (4+ε)-approximation algorithm.     

An approximation algorithm for the m-machine permutation flow shop scheduling problem with controllable processing times

The paper deals with the m-machine permutation flow shop scheduling problem in which job processing times, along with a processing order, are decision variables. It is assumed that the cost of processing a job on each machine is a linear function of its processing time and the overall schedule cost to be minimized is the total processing cost plus maximum completion time cost. A algorithm for the problem with m = 2 is provided; the best approximation algorithm until now has a worst-case performance ratio equal to . An extension to the m-machine (m ≥2) permutation flow shop problem yields an approximation algorithm with a worst-case bound equal to

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, where is the worst-case performance ratio of a procedure used, in the proposed algorithm, for solving the (pure) sequencing problem. Moreover, examples which achieve this bound for = 1 are also presented.     

An approximation algorithm for the generalized assignment problem

The generalized assignment problem can be viewed as the following problem of scheduling parallel machines with costs. Each job is to be processed by exactly one machine; processing jobj on machinei requires timep _ij and incurs a cost ofc _ij ; each machinei is available forT _i time units, and the objective is to minimize the total cost incurred. Our main result is as follows. There is a polynomial-time algorithm that, given a valueC, either proves that no feasible schedule of costC exists, or else finds a schedule of cost at mostC where each machinei is used for at most 2T _i time units.We also extend this result to a variant of the problem where, instead of a fixed processing timep _ij , there is a range of possible processing times for each machine—job pair, and the cost linearly increases as the processing time decreases. We show that these results imply a polynomial-time 2-approximation algorithm to minimize a weighted sum of the cost and the makespan, i.e., the maximum job completion time. We also consider the objective of minimizing the mean job completion time. We show that there is a polynomial-time algorithm that, given valuesM andT, either proves that no schedule of mean job completion timeM and makespanT exists, or else finds a schedule of mean job completion time at mostM and makespan at most 2T. Research partially supported by an NSF PYI award CCR-89-96272 with matching support from UPS, and Sun Microsystems, and by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550.Research supported in part by a Packard Fellowship, a Sloan Fellowship, an NSF PYI award, and by the National Science Foundation, the Air Force Office of Scientific Research, and the Office of Naval Research, through NSF grant DMS-8920550.     

A new approximation algorithm for the multilevel facility location problem

In this paper we propose a new integer programming formulation for the multilevel facility location problem and a novel 3-approximation algorithm based on LP-rounding. The linear program that we use has a polynomial number of variables and constraints, thus being more efficient than the one commonly used in the approximation algorithms for these types of problems.     

A faster 2-approximation algorithm for the minmax p-traveling salesmen problem on a tree

Given an edge-weighted tree T and an integer p1, the minmax p-traveling salesmen problem on a tree T asks to find p tours such that the union of the p tours covers all the vertices. The objective is to minimize the maximum of length of the p tours. It is known that the problem is NP-hard and has a (2−2/(p+1))-approximation algorithm which runs in O(p^p−1n^p−1) time for a tree with n vertices. In this paper, we consider an extension of the problem in which the set of vertices to be covered now can be chosen as a subset S of vertices and weights to process vertices in S are also introduced in the tour length. For the problem, we give an approximation algorithm that has the same performance guarantee, but runs in O((p−1)!·n) time.     

A note on the precedence-constrained class sequencing problem

We give a short proof of a result of Tovey [Non-approximability of precedence-constrained sequencing to minimize setups, Discrete Appl. Math. 134:351-360, 2004] on the inapproximability of a scheduling problem known as precedence-constrained class sequencing. In addition, we present an approximation algorithm with performance guarantee (c+1)/2, where c is the number of colors. This improves upon Tovey's c-approximation.     

An approximation algorithm for the wireless gathering problem

The Wireless Gathering Problem is to find an interference-free schedule for data gathering in a wireless network in minimum time. We present a 4-approximate polynomial-time on-line algorithm for this NP-hard problem. We show that no shortest path following algorithm can have an approximation ratio better than 4.     

A {(\frac 4 3) -} approximation algorithm for a special case of the two machine flow shop problem with several availability constraints

In this paper, we deal with a special case of the two-machine flow shop scheduling problem with several availability constraints on the second machine, under the resumable scenario. We develop an improved algorithm with a relative worst-case error bound of 4/3.     

A 2-approximation for minmax regret problems via a mid-point scenario optimal solution

In this note, a 2-approximation method for minmax regret optimization problems is developed which extends the work of Kasperski and Zielinski [A. Kasperski, P. Zielinski, An approximation algorithm for interval data minmax regret combinatorial optimization problems, Information Processing Letters 97 (2006) 177-180] from finite to compact constraint sets.     

Improved analysis of an algorithm for the coupled task problem with UET jobs

The coupled task problem is to schedule n jobs, each one consisting of two subtasks with exact delay times between them, on a single machine. We derive a new lower bound for the problem variant with unit execution times and correct a previously published analysis.     

A 2.75-approximation algorithm for the unconstrained traveling tournament problem

A 2.75-approximation algorithm is proposed for the unconstrained traveling tournament problem, which is a variant of the traveling tournament problem. For the unconstrained traveling tournament problem, this is the first proposal of an approximation algorithm with a constant approximation ratio. In addition, the proposed algorithm yields a solution that meets both the no-repeater and mirrored constraints. Computational experiments show that the algorithm generates solutions of good quality.